Fin Cascade

Prices as of 8 Oct 2026 close · Not investment advice

Black Box Limited

NSE: BBOXIT Enabled Services

Share price

₹856.55

-3.20% close of 8 Oct 2026

Market cap ₹15,418 CrP/E 53.9

Price-based ratios (P/B, dividend yield, EV/EBITDA) are as of 7 Oct 2026, the close above is 8 Oct 2026.

Business score

How strong the business is, in one number. The parts behind it are in Pro.

57

out of 100 · worked out 8 Oct 2026

Your ratios

The numbers you want to see first. Tap Edit to change them.

Market cap

₹15,418 Cr

P/E ratio

53.9

P/B ratio

11.8

ROCE

21.6%

ROE

25.6%

Dividend yield

0.1%

Price & valuation chart

How the share price and its valuation have moved. Hover over the chart to see any day. Prices as of the last close.

Prices as of 8 Oct 2026 close52-week high ₹1,078.2052-week low ₹447.15

Answers

Simple answers to the questions investors ask most, from the company's own numbers.

How fast it has been growing

Our sales figures for this company step up at Mar 2019 and we hold nothing that says why, so we cannot honestly quote a growth rate across it.

Whether it grew faster than its sector

Our sales figures for this company step up at Mar 2019 and we hold nothing that says why, so there is no honest growth rate of its own to set against its sector.

Room to re-rate, or risk of de-rating

At 53.9× earnings it costs 2.3× the market, which pays 23.9× across 2199 companies we can price. Its own industry sits at 39.0×, across 5 companies. It is against its own five-year median of 36.2×, the 83rd percentile of its own range.

Whether growth justifies the valuation

Priced at 0.7 times its growth rate, on earnings growth of 80%.

Profit growthPrice per ₹1 profitPer 1% growth
Black Box Limited — this one80%/yr53.9×₹0.67
L&T Technology Services Limited6%/yr24.8×₹4.1
Inventurus Knowledge Solutions Limited30%/yr39.0×₹1.3
Tata Technologies Limited-1%/yr43.1×—
Netweb Technologies India Limited64%/yr99.7×₹1.6
SAGILITY LIMITED86%/yr19.7×₹0.23

Compared with companies filed under the same label. That grouping comes from the exchange's filing category, so some of them may not be real rivals.

How it compares with its peers

Against companies the exchange files under the same label (IT Enabled Services), it ranks 16 of 58 on returns, 25 of 54 on growth, 37 of 58 on margin. That grouping comes from the exchange's filing category, so some of them may not be real rivals.

What makes it hard to beat — and is that still true?

A narrow advantage: it earns 21.6% on capital, ahead of 72% of companies filed under the same label. That grouping comes from the exchange's filing category, so some of them may not be real rivals.

Whether its growth pays for itself

Yes — Over the last five years it made ₹233 crore of cash from the business and spent ₹133 crore on plant and equipment, with ₹100 crore to spare; it still raised ₹133 crore mostly borrowed — borrowings rose from ₹481 crore to ₹1153 crore. And the profit is real: of every 100 rupees it reported over 12 years, about 295 arrived as cash — well above the profit; depreciation and interest are the reason, not a windfall. Its cash comes back more slowly than it used to: it went from being paid 29 days before it paid its own suppliers to waiting 54 days for its cash.

Profit reality check

Is the profit real cash? Simple checks on the accounts. Facts only, not advice.

7 of 9 checks clear · 78%

Latest result · Q1 FY27

What the last results showed. Whether management kept its word is in Pro.

Revenue grew 24% in Q1, and management guided FY27 revenue to INR7,800-8,000 crores.

Announced 12 Aug 2026 · Consolidated · Unaudited

Revenue

₹1,719 Cr

Revenue vs last year

+23.9%

Revenue vs last quarter

+1.6%

Net profit

₹56 Cr

Profit vs last year

+19.0%

Profit vs last quarter

-14.0%

Net margin

3.3%

EPS

₹3.15

Earnings call transcript · 13 Aug 2026

Checklist before you investPRO

Points for and against, in one list.

Key numbers & peers

The main numbers grouped by topic, and how the company compares with similar ones.

Price

Market cap
₹15,418 Cr
Prev close
₹856.55
52w High
₹1,103
52w Low
₹444
Enterprise value
₹15,802 Cr
Beta
1.2
Price CAGR 1y
49.0%
Price CAGR 3y
61.0%
Price CAGR 5y
34.0%
Price CAGR 10y
49.0%

Ratios

Return on assets
5.1%
PEG ratio
0.7
P/E ratio
53.9
P/B ratio
11.8
EV / EBITDA
29.3
Industry P/E
26.3
ROCE
21.6%
ROCE 5y average
25.8%
ROE
25.6%
Debt / Equity
0.9
Interest coverage
2.5
Dividend yield
0.1%
ROE 3y average
35.0%
ROE last year
26.0%

Annual P&L

Annual revenue
₹6,322 Cr
Annual profit
₹218 Cr
Operating margin
9.0%
Net profit margin
3.4%
EBITDA margin
8.8%
Sales growth 3y
0.2%
Sales growth 5y
6.2%
Profit growth 3y
80.0%
Profit growth 5y
13.0%
EPS
₹12.3
Sales growth TTM
12.0%
Profit growth TTM
4.0%
Dividend payout
8.0%

Quarter P&L

Sales latest quarter
₹1,719 Cr
Profit latest quarter
₹56 Cr
YoY quarterly sales growth
23.9%
YoY quarterly profit growth
19.1%
OPM latest quarter
9.3%

Balance Sheet

Book Value
₹71.5
Face Value
₹2.0
Total debt
₹1,153 Cr
Total cash
₹540 Cr
Borrowings
₹1,153 Cr
Reserves / Equity
34.8

Cash Flow

Operating cash flow
₹84 Cr
Free cash flow
₹18 Cr
FCF yield
-0.9%
Net cash flow
₹314 Cr

Shareholding

Promoter holding
70.0%
FII holding
4.7%
DII holding
3.4%
Public holding
21.8%

Peer comparison

CompanyPrice ₹P/EMkt cap ₹ CrDiv yield %Profit qtr ₹ CrProfit var %Sales qtr ₹ CrSales var %ROCE %
L&T Technology3,252.1025.734,4891.78357.117.42,940.111.526.7
Inventurus Knowl1,737.4039.129,8380.00193.727.9893.620.731.5
Tata Technolog.697.6043.528,3461.20180.86.21,664.633.820.9
Netweb Technol.4,685.40106.827,8390.0685.3179.9819.7172.137.5
Affle 3i1,436.0042.420,2460.00128.421.7747.220.416.8
Sagility43.1119.720,2320.35216.853.01,963.527.613.4
ESDS Software1,359.00129.315,9550.0029.314.0133.77.330.2
Black Box884.8554.915,6930.1155.920.81,718.523.921.6
Median235.0226.79070.009.221.2111.821.016.6

Competes with: ACS Technologies Limited, Adroit Infotech Limited, Affle 3i Limited, Airan Limited, Allied Digital Services Limited, Amagi Media Labs Limited, Aurum PropTech Limited, BLS E-Services Limited, Bartronics India Limited, Brightcom Group Limited, Cigniti Technologies Limited, Cressanda Railway Solutions Limited, Cyient Limited, DCM Limited, Datamatics Global Services Limited, Dev Information Technology Limited, DiGiSPICE Technologies Limited, Digitide Solutions Limited, Dynacons Systems & Solutions Limited, E2E Networks Limited, ESDS Software Solution Limited, Excelsoft Technologies Limited, Expleo Solutions Limited, FCS Software Solutions Limited, GSS Infotech Limited, Genesys International Corporation Limited, HandsOn Global Management (HGM) Limited, IZMO Limited, Inspirisys Solutions Limited, Intense Technologies Limited, Inventurus Knowledge Solutions Limited, Ivalue Infosolutions Limited, Kellton Tech Solutions Limited, L&T Technology Services Limited, Lee & Nee Softwares Exports Limited, Netweb Technologies India Limited, Odigma Consultancy Solutions Limited, Onward Technologies Limited, Orient Technologies Limited, Palred Technologies Limited, Panache Digilife Limited, Protean eGov Technologies Limited, R Systems International Limited, SAGILITY LIMITED, SECUREKLOUD TECHNOLOGIES LIMITED, SGL Resources Limited, Sasken Technologies Limited, Sigma Solve Limited, Tata Technologies Limited, Tera Software Limited, VEDAVAAG Systems Limited, VL E-Governance & IT Solutions Limited, Vakrangee Limited, Xtranet Technologies Limited, Zaggle Prepaid Ocean Services Limited, eMudhra Limited

Quarterly results

Sales and profit for each of the last 13 quarters. Newest on the right. ₹ crore.

Consolidated · to 30 Jun 2026
Line itemJun 2023Sep 2023Dec 2023Mar 2024Jun 2024Sep 2024Dec 2024Mar 2025Jun 2025Sep 2025Dec 2025Mar 2026Jun 2026
Sales1,5711,5741,6551,4801,4231,4971,5021,5451,3871,5851,6601,6911,719
Expenses1,4841,4761,5411,3551,3091,3651,3681,4021,2711,4421,5131,5271,559
Material Cost1.063.04320.490.030.46
Change in Inventories11-7.17-205184628
Purchases of Stock-in-Trade536476748570545496
Employee Cost520532549587572656
Other Expenses329266318337363378
Operating Profit8799114125115133134143116143147164160
OPM %5.556.276.898.448.068.868.909.258.389.018.859.719.30
Other Income-2-52-8-14-17-12-10-11-13-21-12-15
Exceptional items (within Other Income)-16-13-14-22-14-19
Interest33323640343231473439404548
Depreciation28292829262831282729303136
Profit before tax24335247405559584561577661
Tax %242113865-5-5912159
Net Profit24324141375156604756506556
EPS in Rs1.431.902.432.432.213.043.313.572.793.272.923.653.15
Diluted EPS in Rs3.542.793.252.893.753.15

Profit & loss

Yearly sales, costs and profit for 12 years, plus the last 12 months (TTM). ₹ crore.

Consolidated · to 31 Mar 2026
Line itemMar 2015Mar 2016Mar 2017Mar 2018Mar 2019Mar 2020Mar 2021Mar 2022Mar 2023Mar 2024Mar 2025Mar 2026TTM
Sales8918817807331,8534,9944,6745,3706,2886,2825,9676,3226,654
Expenses8678767477001,8064,6664,3105,1126,0145,8555,4295,7656,040
Material Cost2.653.41
Change in Inventories36-115
Purchases of Stock-in-Trade1,8002,338
Employee Cost2,2792,241
Other Expenses1,3191,285
Operating Profit246323347328364258273426538557614
OPM %2.700.704.204.502.50784.804.307999
Other Income3871319-67-178-750-25-14-68-44-61
Exceptional items (within Other Income)-66-63
Interest26272625451329874111141145158172
Depreciation1887815929699107114113116125
Profit before tax18-221319-79-73968629156212239255
Tax %16551822-1101915201239
Net Profit15-351015-79-80787324138205218226
EPS in Rs1.04-2.430.731.05-5.30-5.384.804.431.418.19121213
Diluted EPS in Rs1213
Dividend Payout %-0-0-0-0-0-0-0-0-0-088

Compounded growth

Average yearly growth over different spans, as stored. A span can cross a demerger or an acquisition.

Compounded sales growth

10 years
22%
5 years
6%
3 years
0%
TTM
12%

Compounded profit growth

10 years
25%
5 years
13%
3 years
80%
TTM
4%

Stock price CAGR

10 years
49%
5 years
34%
3 years
61%
1 year
49%

Return on equity

10 years
—
5 years
32%
3 years
35%
Last year
26%

Balance sheet

What the company owns and what it owes, at the end of each year. ₹ crore.

Consolidated
Line itemMar 2015Mar 2016Mar 2017Mar 2018Mar 2019Mar 2020Mar 2021Mar 2022Mar 2023Mar 2024Mar 2025Mar 2026
Equity Capital282828283030333334343436
Reserves58254147-11-2061742282624477251,251
Borrowings1611771731588085963284816287129421,153
Other Liabilities3853933463461,6051,8861,7681,9112,0781,6071,3711,854
Minority Interest00
Total Liabilities6336235895802,4322,3062,3032,6523,0022,8003,0724,294
Fixed Assets90109111114399557622732794808769883
CWIP-0-0-0-0-0-0-0-02-0-0-0
Investments-0-0-0-0-0-0-0-0303233-0
Other Assets5435144784672,0321,7491,6811,9202,1751,9602,2713,410
Total Assets6336235895802,4322,3062,3032,6523,0022,8003,0724,294

Cash flows

Real money coming in and going out each year — from the business, from investments and from loans. ₹ crore.

Consolidated
Line itemMar 2015Mar 2016Mar 2017Mar 2018Mar 2019Mar 2020Mar 2021Mar 2022Mar 2023Mar 2024Mar 2025Mar 2026
Cash from Operating Activity2829452-721,1373039513129-8884
Cash from Investing Activity77-21-4-5-360-38215-108-5640-10533
Cash from Financing Activity-100-10-11-54629-645-277-43-58-155192197
Net Cash Flow5-2-10-719711041-55-10214-0314
Free Cash Flow2420-541-3651,0812854532134-12918

Ratios

How fast customers pay, how long stock sits, and how well capital earns — year by year.

Consolidated
Line itemMar 2015Mar 2016Mar 2017Mar 2018Mar 2019Mar 2020Mar 2021Mar 2022Mar 2023Mar 2024Mar 2025Mar 2026
Debtor Days101909710417026192524223567
Inventory Days252324478833354765504253
Days Payable187184187209324133122210208146110129
Cash Conversion Cycle-60-71-66-59-65-73-68-137-118-74-34-10
Working Capital Days-40-61-61-29-5-59-43-29-1323354
ROCE %411213739582620313022

Shareholding pattern

Who owns the company — founders (promoters), foreign funds, Indian funds and the public. In %.

Consolidated · to 30 Jun 2026
Line itemSep 2023Dec 2023Mar 2024Jun 2024Sep 2024Dec 2024Mar 2025Jun 2025Sep 2025Dec 2025Mar 2026Jun 2026
Promoters717171717171717070707070
FIIs4.924.834.814.713.384.334.704.094.223.433.264.69
DIIs0.010.010.010.010.020.020.030.030.042.462.993.41
Government0.130.130.130.130.130.130.130.130.130.130.120.12
Public242424242525252525242422
No. of Shareholders16,84716,39416,64726,20655,99760,19864,21078,70988,06581,63973,63872,559

Price trend

The price as a Renko brick chart: small moves drop out so the bigger path stands out.

Change over 1 year +56.3% (₹548.00 → ₹856.55)Brick size ₹43.28 (fixed)Bricks 24
₹600₹1,000₹857Mar '26Jun '26Oct '26
Price moved up one brickPrice moved down one brickLast close ₹856.55 on 8 Oct 2026

Every brick is the same size, about one typical day's move. A new brick needs a full brick's move; turning the other way needs two. Bricks show where the price went, not where it will go.

Open interestPRO

Where option traders are positioned on this stock.

Industry numbers

The numbers that matter most in this industry, from the company's own filings.

1 when an audit qualification is filed as repetitive

0.00flag

2026-03-31

the company's own unlisted debt securities in default at period end

0.00cr

2026-06-30

the company's own loans / revolving facilities in default at period end (standalone filing)

0.00cr

2026-06-30

guarantees / comfort given for promoter, promoter group, directors and KMP

0.00cr

2026-03-31

loans outstanding to promoter, promoter group, directors and KMP (governance filing)

0.00cr

2026-03-31

security given for the borrowing of promoter, promoter group, directors and KMP

0.00cr

2026-03-31

FY revenue / permanent employees + workers, same basis (calc)

2,15,69,430inr

2026-03-31

News

News and filings about Black Box Limited. Open one to see why it matters.

No recent news for this company.

Supply chain

Who it buys from, sells to and competes with — as recorded in our map of company links.

About

What the company is, from our own records: where it sits, where it makes things, and what it is made of.

Sector
Information Technology
Industry
IT Enabled Services
Classification
Information Technology › IT Enabled Services
ISIN
INE676A01027

Business segments

  • System integration · 84%
  • Technology product solutions · 13%
  • Others · 2%

News impact

Big market events that reach Black Box Limited, and how the effect spreads.

Who it hits first

  • ESDS Software Solution (cloud hosting) reported Q1 FY27 net profit of Rs 29.3 crore, down 57% from the prior quarter, and its shares hit the 5% lower circuit at Rs 1,758.
  • Holders who bought after the multibagger IPO run face sharp losses as analysts advise fresh investors to avoid chasing and allotted investors to book partial profits.

Who may gain

  • No clear near-term beneficiary — this is a company-specific profit miss at ESDS, not a demand shift toward rivals.

Along the supply chain

Downstream

No direct downstream link — ESDS cloud customers face no stated price or outage change, so their costs and buying plans stay put.

Upstream

No direct upstream link — ESDS named no hardware or software supplier impact, and server or chip vendors face no stated order change from this profit miss.

Where demand moves

Business

Business demand does not move: ESDS cloud customers have no stated reason to switch, and no rival names an order gain, so this stays a profit-margin story, not a demand shift.

Capital

Capital flows out of ESDS as momentum holders sell into the lower circuit, with some money pausing on richly priced small IT names such as Netweb Technologies and E2E Networks until the next updates.

How it spreads across sectors

Information Technology

Small high-multiple IT stocks wobble on sympathy selling as ESDS resets growth hopes, while large IT services names see no order impact.

When it plays out

Immediate

ESDS stays weak and choppy near circuit limits as holders exit; close cloud peer E2E Networks and infra name Netweb Technologies trade soft on sympathy.

Medium term

ESDS must rebuild profit growth to defend its premium; rivals move on their own orders, with any lasting share shift to E2E Networks only if ESDS delivery slips.

Short term

Direction follows ESDS management commentary and peer updates: steady guidance calms the group, while weak follow-through extends derating of rich small IT names.

Who it hits first

  • Staffing-heavy outsourcers face higher onsite costs and compliance burden
  • Majors (TCS, Infosys) see headline risk and FII selling, but localized workforces limit real damage
  • Domestic/product IT names (cloud, SaaS, servers) are unaffected

Who may gain

  • US staffing and localization plays; domestic GCCs (global capability centers) gain talent
  • Indian product/SaaS firms hiring returning engineers

Along the supply chain

Downstream

US clients pay slightly more for compliant delivery or accept more offshore mix.

Upstream

No goods chain — the 'supply' is skilled engineers, whose US mobility narrows; offshore benches deepen instead.

Where demand moves

Business

US clients shift marginal work offshore or to local hires, trimming onsite billing; domestic GCC hiring absorbs returning engineers over 2-4 quarters.

Capital

FII trims IT majors on visa headlines; domestic funds buy the dip as earnings impact proves small — the post-2017 pattern.

How it spreads across sectors

Information Technology

mildly negative on costs and sentiment; structural offshoring trend intact

When it plays out

Immediate

IT stocks dip 1-2% on headlines; FII selling concentrated in majors

Medium term

Localization deepens; 60-day-grace rule (if finalized) is the bigger structural risk

Short term

Q2 management commentary quantifies cost impact (likely <50 bps margins)

Who it hits first

  • No Indian company is NVIDIA; all exposure is second-order. Indian AI-server/HPC integrators (NETWEB) and chip/embedded-design firms (MOSCHIP, TATAELXSI) get a demand tailwind from the next-gen NVIDIA GPU platform.
  • IT services majors (TCS, INFY) face a two-sided impact: more AI-implementation/transformation demand vs faster automation of traditional services.

Who may gain

  • NETWEB — GPU/HPC server integration
  • BBOX — data-center and IT-infrastructure build-out
  • MOSCHIP — semiconductor/ASIC design
  • TATAELXSI — AI/embedded design services

Along the supply chain

Downstream

Downstream, Indian enterprises, data-center operators and cloud/sovereign-AI buyers consume the new compute; cheaper/faster AI compute lowers their input cost and accelerates AI deployment, feeding services demand at TCS/INFY and infrastructure demand at BBOX.

Upstream

Upstream sits offshore — NVIDIA (TSMC-fabbed GPUs) is above every Indian name; Indian AI-server assemblers (NETWEB) and EMS players are downstream GPU buyers, so any advanced-GPU supply tightness or allocation limits could ration their kit availability.

Where demand moves

Business

New demand is created for GPU-server integration (NETWEB), data-center build-out (BBOX), chip/embedded design (MOSCHIP, TATAELXSI) and AI-implementation services (TCS, INFY). No Indian supplier loses business directly because none competes with NVIDIA; the platform is an input that lowers AI compute cost for downstream Indian buyers.

Capital

Capital rotates toward the AI-infrastructure theme — high-beta AI-server and chip-design small/mid-caps (NETWEB beta 1.72, MOSCHIP beta 1.11) absorb momentum flows first, while large-cap IT (TCS, INFY) acts as a cheaply-valued defensive anchor rather than a momentum leader.

How it spreads across sectors

IT Services

Mixed — AI-transformation services opportunity vs automation cannibalization of legacy work

Information Technology

Positive demand for AI-infrastructure build-out and AI services

Power

AI compute capacity expansion lifts data-center electricity demand over the medium term

codex additions

  • Data Centers & Digital Infrastructure
  • Electrical Equipment, Cables & Grid Hardware
  • Cooling, HVAC & Thermal Management
  • Electronics Manufacturing Services & Server Hardware
  • Telecom & Network Infrastructure
  • Industrial Automation & Capital Goods
  • Education, Skilling & Staffing
  • BFSI Technology Users
  • Water Treatment & Utilities for Data Centers

A pattern seen before

Cascade chain

  • NVIDIA next-gen GPU platform launch
  • AI-server / GPU-cluster demand rises (NETWEB, EMS)
  • Data-center build-out accelerates (BBOX, data-center developers)
  • Power, cooling and electrical-equipment capex follows
  • Chip/embedded-design services demand rises (MOSCHIP, TATAELXSI)
  • IT-services AI-implementation demand vs automation offset (TCS, INFY)

Pattern name

Semiconductor Cascade

Sectors queried

  • Information Technology
  • IT Services
  • Data Centers & Digital Infrastructure
  • Electronics Manufacturing Services
  • Power
  • Cooling/HVAC
  • Telecom

When it plays out

Immediate

Sentiment pop in Indian AI-infra/server names (NETWEB, MOSCHIP) on the announcement; muted, headline-driven move for large-cap IT given the second-order, US-centric catalyst.

Medium term

A sustained AI-capex cycle lifts data-center, EMS, power and cooling demand; for IT services the automation-vs-implementation balance determines whether AI is net-accretive to revenue.

Short term

Watch for India deployment commitments (sovereign-AI / hyperscaler / enterprise capex) that convert the theme into actual order flow for server assemblers and data-center infrastructure.

Other sectors it reaches

  • {"causal_chain":"Next-gen NVIDIA AI platforms increase demand for high-density GPU clusters -\u003e hyperscalers, enterprises and sovereign-AI programs need more Indian data-center capacity -\u003e listed data-center/infra providers benefit from higher leasing and capex.","direction":"positive","example_tickers":["ANANTRAJ","BBOX","TATACOMM"],"magnitude":"large","notes":"Most direct missed sector after IT; benefit depends on actual Indian deployment pace and power availability. Suggested by Codex Layer 5.5.","sector":"Data Centers \u0026 Digital Infrastructure","time_horizon":"1_to_6_months"}
  • {"causal_chain":"AI data centers require higher power density, substations, transformers, switchgear, UPS and cabling -\u003e data-center capex flows into electrical equipment and power-distribution suppliers.","direction":"positive","example_tickers":["SIEMENS","ABB","POLYCAB"],"magnitude":"medium","notes":"Second-order capex beneficiary; order visibility may lag headlines. Suggested by Codex Layer 5.5.","sector":"Electrical Equipment, Cables \u0026 Grid Hardware","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Higher-performance GPUs increase rack power density and heat load -\u003e data centers need advanced cooling, chillers and precision air-conditioning -\u003e HVAC suppliers see incremental demand.","direction":"positive","example_tickers":["BLUESTARCO","VOLTAS","AMBER"],"magnitude":"medium","notes":"Magnitude rises with liquid-cooling adoption in Indian AI data centers. Suggested by Codex Layer 5.5.","sector":"Cooling, HVAC \u0026 Thermal Management","time_horizon":"1_to_6_months"}
  • {"causal_chain":"AI-server demand grows around the new NVIDIA architecture -\u003e more local assembly, PCB, enclosure, power-module and systems-integration work -\u003e EMS firms benefit from localization tailwinds.","direction":"positive","example_tickers":["KAYNES","SYRMA","DIXON"],"magnitude":"medium","notes":"Strongest where firms have enterprise-electronics or server-adjacent manufacturing. Suggested by Codex Layer 5.5.","sector":"Electronics Manufacturing Services \u0026 Server Hardware","time_horizon":"1_to_6_months"}
  • {"causal_chain":"AI workloads increase data traffic between users, edge nodes, clouds and data centers -\u003e demand rises for fiber, optical gear and data-center interconnects -\u003e telecom and network-equipment suppliers benefit.","direction":"positive","example_tickers":["BHARTIARTL","TEJASNET","STLTECH"],"magnitude":"medium","notes":"Indirect but defensible via cloud connectivity and edge-AI. Suggested by Codex Layer 5.5.","sector":"Telecom \u0026 Network Infrastructure","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Faster AI compute improves industrial AI, robotics and digital-twin adoption -\u003e manufacturers invest in automation hardware and control systems -\u003e automation/capital-goods suppliers get a demand tailwind.","direction":"positive","example_tickers":["CGPOWER","HONAUT","SCHNEIDER"],"magnitude":"small","notes":"Third-order adoption effect, not an immediate catalyst. Suggested by Codex Layer 5.5.","sector":"Industrial Automation \u0026 Capital Goods","time_horizon":"1_to_6_months"}
  • {"causal_chain":"New AI infrastructure accelerates enterprise AI adoption -\u003e demand rises for AI engineers, cloud architects and reskilling -\u003e education/staffing platforms see higher course and placement demand.","direction":"positive","example_tickers":["NIITLTD","TEAMLEASE","NAUKRI"],"magnitude":"small","notes":"Offset risk: AI automation can reduce demand for lower-end staffing roles. Suggested by Codex Layer 5.5.","sector":"Education, Skilling \u0026 Staffing","time_horizon":"1_to_6_months"}
  • {"causal_chain":"More powerful AI infrastructure enables faster deployment of fraud analytics, underwriting automation and risk models -\u003e banks/insurers gain productivity but also face higher tech spend.","direction":"mixed","example_tickers":["HDFCBANK","ICICIBANK","SBILIFE"],"magnitude":"small","notes":"Benefits accrue via productivity, not direct NVIDIA-hardware revenue. Suggested by Codex Layer 5.5.","sector":"BFSI Technology Users","time_horizon":"1_to_6_months"}
  • {"causal_chain":"AI data-center expansion increases requirements for cooling water, wastewater handling and utility-grade treatment -\u003e water-infrastructure firms see project opportunities around large campuses.","direction":"positive","example_tickers":["WABAG","IONEXCHANG","THERMAX"],"magnitude":"small","notes":"Relevant where data centers use water-intensive cooling. Suggested by Codex Layer 5.5.","sector":"Water Treatment \u0026 Utilities for Data Centers","time_horizon":"1_to_6_months"}

Who it hits first

  • Indian IT-services / SaaS-automation vendors face a cheaper native agentic-AI substitute for custom automation and RPA-style deliverables
  • ER&D/design-services (TATAELXSI) and SaaS-product automation (CAPILLARY, AMAGI) face commoditization of agentic workflows
  • Note: Alphabet/Google are US-listed and not in the Indian knowledge graph — the India impact is an indirect 2nd-order competitive pressure on the IT cluster, not a direct corporate event on a domestic name

Who may gain

  • AI-infrastructure / HPC server builders (NETWEB) gain from rising AI inference-compute demand
  • Cybersecurity and enterprise adopters benefit as agentic adoption expands the attack surface and lowers automation cost

Along the supply chain

Downstream

Downstream enterprise buyers (BFSI, retail, GCCs) gain a cheaper native automation substitute, pressuring per-seat/per-project pricing on mid-tier IT automation and RPA-style deliverables.

Upstream

Indian IT vendors' upstream is cloud/compute capacity (hyperscaler inference) and AI-model APIs; a cheaper native agentic model raises reliance on hyperscaler compute, shifting value upstream toward compute/data-centre and AI-server providers (NETWEB) and away from custom-automation labour.

Where demand moves

Business

Demand for bespoke agentic-automation builds shifts toward off-the-shelf Gemini computer-use; ER&D/SaaS-automation vendors (TATAELXSI, CAPILLARY, AMAGI) face substitution while AI-infrastructure builders (NETWEB) capture incremental inference-compute demand.

Capital

Capital rotates out of high-multiple Indian IT/tech names on AI-disruption fear (a DeepSeek-style de-rating), favouring AI-infrastructure/compute beneficiaries over labour-arbitrage automation plays.

How it spreads across sectors

IT Services

negative — agentic AI commoditizes mid-tier automation deliverables, pricing pressure on labour-arbitrage models

Information Technology

mixed — negative for pure-automation/services, positive for AI-infrastructure (compute, servers, data centres)

codex additions

  • BPM / BPO / KPO Services
  • Telecom / Connectivity
  • Data Centers / Digital Infrastructure
  • Power Utilities / Grid Equipment
  • Electrical & Cooling Equipment
  • Electronics Manufacturing / EMS
  • Cybersecurity
  • Banking & Financial Services
  • Staffing / Recruitment / HR Services
  • Education / Skilling

When it plays out

Immediate

Limited direct India price reaction expected (US product launch); modest sentiment pressure on high-multiple AI-exposed IT names, partial offset to AI-infra names like NETWEB.

Medium term

Structural commoditization risk for labour-arbitrage automation deliverables; AI-infrastructure and reskilling/cybersecurity beneficiaries strengthen.

Short term

Watch enterprise/GCC commentary on adopting native agentic tools vs custom IT builds; pricing pressure signals on automation deals.

Other sectors it reaches

  • {"causal_chain":"Native computer-use agents automate browser, form-filling, reconciliation, support-ticket and back-office workflows -\u003e enterprises reduce dependence on labor-heavy managed process outsourcing -\u003e margin and volume pressure for routine BPM/KPO providers, partly offset by AI-managed service demand.","direction":"negative","example_tickers":["MPHASIS","PERSISTENT","LTIM"],"magnitude":"medium","notes":"Listed pure-play BPO exposure is limited on NSE, so tickers are IT/BPM-adjacent names with enterprise operations exposure. | Suggested by Codex Layer 5.5","sector":"BPM / BPO / KPO Services","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Agentic AI adoption increases API calls, cloud workloads, enterprise SaaS usage and edge connectivity needs -\u003e higher data traffic and enterprise connectivity demand -\u003e telecom operators benefit from network, cloud-connect and enterprise digital services spend.","direction":"positive","example_tickers":["BHARTIARTL","IDEA","TATACOMM"],"magnitude":"medium","notes":"Benefit is indirect and depends on monetization of enterprise data/cloud connectivity rather than consumer tariffs. | Suggested by Codex Layer 5.5","sector":"Telecom / Connectivity","time_horizon":"1_to_6_months"}
  • {"causal_chain":"More agentic workloads shift automation from local/manual execution to cloud-hosted inference and orchestration -\u003e demand rises for data-center capacity, power-dense racks, networking and managed hosting -\u003e Indian digital infra providers see stronger utilization and capex cycles.","direction":"positive","example_tickers":["ANANTRAJ","TATACOMM","RAILTEL"],"magnitude":"medium","notes":"Strongest for companies with actual or planned data-center/cloud infrastructure exposure. | Suggested by Codex Layer 5.5","sector":"Data Centers / Digital Infrastructure","time_horizon":"1_to_6_months"}
  • {"causal_chain":"AI inference and data-center expansion raise electricity demand and power-quality requirements -\u003e utilities and grid equipment suppliers benefit from incremental load, transmission upgrades and backup-power investments.","direction":"positive","example_tickers":["NTPC","POWERGRID","TATAPOWER"],"magnitude":"medium","notes":"Second-order impact; magnitude grows if AI data-center buildout accelerates materially in India. | Suggested by Codex Layer 5.5","sector":"Power Utilities / Grid Equipment","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Higher AI-server and data-center density increases demand for UPS systems, transformers, switchgear, precision cooling and thermal-management equipment -\u003e order books improve for electrical capital goods and cooling suppliers.","direction":"positive","example_tickers":["VOLTAS","BLUESTARCO","ABB"],"magnitude":"medium","notes":"More direct than utilities where data-center capex translates into equipment orders. | Suggested by Codex Layer 5.5","sector":"Electrical \u0026 Cooling Equipment","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Enterprise AI adoption drives demand for servers, endpoints, networking devices and specialized hardware assembly -\u003e domestic EMS players may benefit from localization, PLI-linked manufacturing and enterprise hardware refresh cycles.","direction":"positive","example_tickers":["DIXON","KAYNES","SYRMA"],"magnitude":"medium","notes":"Upside depends on how much AI hardware assembly is localized versus imported. | Suggested by Codex Layer 5.5","sector":"Electronics Manufacturing / EMS","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Computer-use agents can interact with browsers, apps and credentials -\u003e attack surface expands through prompt injection, automated phishing, session misuse and data leakage -\u003e enterprises increase spend on identity, endpoint, SOC and application security.","direction":"positive","example_tickers":["TANLA","NEWGEN","RATEGAIN"],"magnitude":"small","notes":"India has few pure-play listed cybersecurity names; tickers are security, workflow or enterprise-software adjacent. | Suggested by Codex Layer 5.5","sector":"Cybersecurity","time_horizon":"1_to_4_weeks"}
  • {"causal_chain":"Banks, insurers and lenders can use GUI/browser agents for onboarding, KYC checks, claims, collections, reconciliations and customer service -\u003e operating cost improves, but vendor pricing pressure and model-risk/compliance costs rise.","direction":"mixed","example_tickers":["HDFCBANK","ICICIBANK","SBIN"],"magnitude":"medium","notes":"Large private banks may benefit most from automation scale; near-term impact is more cost-efficiency narrative than immediate earnings. | Suggested by Codex Layer 5.5","sector":"Banking \u0026 Financial Services","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Agentic AI reduces demand for routine coding, testing, support and back-office roles while increasing demand for AI governance and integration talent -\u003e IT staffing mix shifts and billable headcount growth may slow.","direction":"negative","example_tickers":["TEAMLEASE","QUESS","SIS"],"magnitude":"medium","notes":"Pressure is strongest for contract staffing tied to repetitive IT support and process roles. | Suggested by Codex Layer 5.5","sector":"Staffing / Recruitment / HR Services","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Rapid commoditization of automation work increases reskilling demand in AI operations, prompt engineering, governance, cybersecurity and cloud infrastructure -\u003e training platforms and education providers can see higher course demand.","direction":"positive","example_tickers":["NIITLTD","APTECHT","VERANDA"],"magnitude":"small","notes":"Positive but execution-dependent; consumer willingness to pay and placement outcomes matter. | Suggested by Codex Layer 5.5","sector":"Education / Skilling","time_horizon":"1_to_6_months"}

Who it hits first

  • No Indian-listed company is directly named — Anthropic is a US-private firm absent from the knowledge graph (analyzed from article content only).
  • US is close to reversing its June 12, 2026 export-control order that disabled Anthropic's Fable 5 frontier AI model for 15 days, normalizing global frontier-AI tooling availability.

Who may gain

  • Indian IT-services and GenAI-integration plays that build products on frontier models see a marginal, sentiment-level positive as AI delivery pipelines are de-risked — no direct revenue channel.

Along the supply chain

Downstream

Downstream Indian IT/GenAI integrators that embed frontier models in client deliverables (design engineering, cloud SI, media-SaaS) regain uninterrupted tooling; impact is delivery-continuity, not volume shortage.

Upstream

No physical upstream supply chain — frontier AI models are a software/API input; the only 'upstream' is access to the US-developed model itself, which restoration normalizes for Indian developer-consumers.

Where demand moves

Business

Restored frontier-AI model access removes a 15-day supply overhang on AI tooling used by Indian GenAI integrators (TATAELXSI, SILVERTUC, BBOX) for delivery; demand effect is indirect and accrues to AI-services pipelines rather than any disrupted physical supply chain.

Capital

Mild risk-on rotation into Indian AI-themed IT names as a US AI-policy overhang lifts; flows are sentiment-driven and likely concentrate in liquid mid/small-cap IT (NETWEB, TATAELXSI) rather than producing durable capital reallocation.

How it spreads across sectors

IT Services

Mild positive — AI-led delivery pipelines de-risked

Information Technology

Mild positive — frontier-AI tooling supply normalizes for GenAI-integration plays

codex additions

  • Data centres and digital infrastructure
  • Telecom and internet connectivity
  • Electronics manufacturing and AI hardware
  • Power equipment, cooling and electrical infrastructure
  • Cybersecurity and digital risk management
  • Banking and financial services
  • Education, skilling and training
  • Media, advertising and digital content
  • Pharma R&D and contract research

When it plays out

Immediate

Marginal positive sentiment for liquid AI-themed Indian IT names on the headline; no direct earnings impact.

Medium term

Normalized frontier-AI access supports the structural Indian GenAI-services and data-centre buildout theme; effect is diffuse and not company-specific.

Short term

If the reversal is confirmed, GenAI-integration narratives firm up; watch for AI-deal commentary in IT-services Q1 results.

Other sectors it reaches

  • {"causal_chain":"Restored frontier-AI access -\u003e Indian enterprises resume GenAI pilots -\u003e higher cloud inference, storage and hosting demand -\u003e incremental demand for data-centre capacity and managed infrastructure","direction":"positive","example_tickers":["ANANTRAJ","TATACOMM","NETWEB"],"magnitude":"medium","notes":"Most impact is sentiment and demand-expectation led; stronger for companies already linked to data centres or AI compute.","sector":"Data centres and digital infrastructure","time_horizon":"1_to_6_months"}
  • {"causal_chain":"AI tooling normalization -\u003e more enterprise AI workloads and API usage -\u003e higher data traffic, leased lines, edge connectivity and enterprise network demand","direction":"positive","example_tickers":["BHARTIARTL","INDUSTOWER","TATACOMM"],"magnitude":"small","notes":"Likely diffuse, not a direct earnings trigger, but supports enterprise connectivity narratives.","sector":"Telecom and internet connectivity","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Frontier-model availability improves confidence in AI deployment -\u003e enterprises and cloud vendors expand servers, edge devices and high-end electronics procurement -\u003e benefits EMS and AI-server supply-chain names","direction":"positive","example_tickers":["DIXON","KAYNES","SYRMA"],"magnitude":"medium","notes":"India-listed exposure is mostly indirect through EMS and specialized electronics rather than frontier GPUs.","sector":"Electronics manufacturing and AI hardware","time_horizon":"1_to_6_months"}
  • {"causal_chain":"More AI compute adoption -\u003e higher data-centre power density and cooling needs -\u003e demand for electrical systems, automation, HVAC and backup power infrastructure","direction":"positive","example_tickers":["ABB","SIEMENS","BLUESTAR"],"magnitude":"small","notes":"Second-order capex linkage; materiality depends on actual data-centre buildout.","sector":"Power equipment, cooling and electrical infrastructure","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Restored powerful AI tools -\u003e faster enterprise GenAI adoption plus greater phishing, code-generation and data-leak risks -\u003e demand for endpoint security, audits and secure AI governance","direction":"positive","example_tickers":["QUICKHEAL","TANLA","ROUTE"],"magnitude":"small","notes":"Positive for security demand, but also raises operational-risk concerns for AI-exposed firms.","sector":"Cybersecurity and digital risk management","time_horizon":"1_to_4_weeks"}
  • {"causal_chain":"Stable access to frontier models -\u003e banks and insurers restart AI automation in underwriting, customer service, fraud detection and document processing -\u003e productivity and digital-transformation sentiment improves","direction":"positive","example_tickers":["HDFCBANK","ICICIBANK","SBIN"],"magnitude":"small","notes":"Large institutions benefit through efficiency optionality; near-term earnings impact is limited.","sector":"Banking and financial services","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Frontier-AI availability normalizes -\u003e demand for GenAI training, corporate upskilling and AI-assisted learning products resumes -\u003e benefits listed education and training providers","direction":"positive","example_tickers":["NIITLTD","APTECHT","VERANDA"],"magnitude":"medium","notes":"Smaller sector, so sentiment sensitivity can be higher despite indirect linkage.","sector":"Education, skilling and training","time_horizon":"1_to_4_weeks"}
  • {"causal_chain":"Restored generative models -\u003e lower creative production costs and faster ad/content workflows -\u003e benefits digital content and ad-tech users, while increasing competitive pressure on legacy content economics","direction":"mixed","example_tickers":["NAZARA","ZEEL","PVRINOX"],"magnitude":"small","notes":"Productivity upside is offset by IP, authenticity and content-commoditization risks.","sector":"Media, advertising and digital content","time_horizon":"1_to_6_months"}
  • {"causal_chain":"Frontier-AI access normalizes -\u003e AI-assisted molecule screening, literature review and trial analytics workflows face less disruption -\u003e marginal positive for R\u0026D-heavy pharma and CRAMS names","direction":"positive","example_tickers":["SUNPHARMA","DRREDDY","SYNGENE"],"magnitude":"small","notes":"Causal link is plausible but slow-moving; not an immediate trading catalyst.","sector":"Pharma R\u0026D and contract research","time_horizon":"1_to_6_months"}

Dividends, splits & big trades

Money paid out, share splits and buybacks, and big buys or sells by funds and insiders.

Dividends

28 Aug 2026unspecified₹1
29 Aug 2025unspecified₹1
13 May 2022split₹0
19 Dec 2012bonus₹0
16 Jul 2012unspecified₹15
8 Jul 2011unspecified₹2.25

Splits, bonuses & buybacks

  • daily-prices repair: 10 rows from NSE's archive (replace 2, delete 1, insert 7), 2016-10-30..2026-02-01 (docs/flat_day_repair.md)1× · 30 Oct 2016

Documents

Annual reports, results presentations and earnings calls, straight from the source.

Facts from company filings and exchange data. Not investment advice: nothing here tells you to buy or sell.