ABI NexaIntelligence OS
The data & access layer
ΣFundamentals & Filings DataStandardized and as-reported, citedfxExcel Add-inThe cited number in your model{ }Data APIThe whole corpus, programmatic∞MCP ServerThe AI-native connector⛱Research WorkspaceThe whole file, per name
AI-native deliverables
ΣOperating & Valuation ModelsBuilt, sourced, refreshed on the print▤Company Tearsheets & ProfilesThe as-of-date one-pager✎Confidential Information MemorandaThe sell-side document, drafted✎Investment MemorandaThe buy-side write-up, traceable▣Pitch BooksProfiles and precedents, quoted⚟Screening & Idea GenerationScreens across the corpus
Who we serve
BBuy-SideHedge funds & asset managersSSell-Side ResearchEquity researchIBInvestment Banking & Corp DevM&A and coveragePEPrivate Equity & VCDeal teams, diligence to model▣CorporatesStrategy, IR and FP&A{ }Data & Quant TeamsAgents and pipelines
Plans Methodology Resources Sign in Request access
Products
Fundamentals & Filings DataStandardized and as-reported, citedExcel Add-inThe cited number in your modelData APIThe whole corpus, programmaticMCP ServerThe AI-native connectorResearch WorkspaceThe whole file, per name
Solutions
Operating & Valuation ModelsBuilt, sourced, refreshed on the printCompany Tearsheets & ProfilesThe as-of-date one-pagerConfidential Information MemorandaThe sell-side document, draftedInvestment MemorandaThe buy-side write-up, traceablePitch BooksProfiles and precedents, quotedScreening & Idea GenerationScreens across the corpus
Clients
Buy-SideHedge funds & asset managersSell-Side ResearchEquity researchInvestment Banking & Corp DevM&A and coveragePrivate Equity & VCDeal teams, diligence to modelCorporatesStrategy, IR and FP&AData & Quant TeamsAgents and pipelines
PlansMethodologyResources
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AI-Native Solution

Use a model already built, or refresh your own.

A driver-based three-statement model and valuation, already built on the provenanced corpus, every historical cell naming its filing, and refreshed the moment a company reports.

Request accessSee the platform
See it

A real model, forecast the way each business works.

Real, cited ABI Nexa output. Use the arrows or dots to move through.

Football field valuation
The valuation spread across every method
Every valuation method the platform computes, each shown as a range, so the spread of fair value is visible at a glance rather than collapsed into a single number.
DCF, base case
131-178
EV / Revenue
68-172
EV / EBITDA
72-151
EV / EBIT
63-157
Price / Revenue
62-139
Price / BVPS
78-145
Price / Earning
87-121
52-week high/low
78-109

Per-share values in EUR, low to high by method. ABI Nexa research, from company filings.

Banking forecast
Built on net interest income and fees
A bank is forecast the way it earns: net interest income off the earning-asset base and deposit margin, plus fee income, down to pre-provision revenue. Not a single revenue line with a growth rate on top.
Bank P&L build, $MFY2025A to FY2028E
DriverFY25AFY26EFY27EFY28E
Net interest income95,443106,896118,762130,875
Fee (noninterest) income87,00492,08397,198102,320
Noninterest expense95,640102,911110,260117,628
Pre-provision revenue86,80796,069105,699115,567
NII grown 12.0% on the earning-asset base and a Banking & Wealth deposit margin of 1.7%; fee income 5.8%. JPMorgan 10-K, accession 0001628280-26-008131.
KPI-driven forecast
Subscribers times ARPU, not a growth rate
Jio's Digital Services revenue is forecast off the operating KPIs it discloses, its subscriber base times ARPU, so the forecast moves the way the business does.
488.2M
Total customer base
+6.1M net adds in the quarter
₹206.2
ARPU, per month
churn 1.8%
Digital Services revenue, ₹Mnsubs × ARPU
LineBaseYr1Yr2Yr3Yr4
Segment revenue1,329,3801,537,6941,735,7181,910,7652,050,117
Growth15.7%12.9%10.1%7.3%
Reliance Industries investor presentation, 24 April 2026.
DCF valuation
A full DCF table, built with sensitivity
A discounted cash flow, forecast from revenue down to unlevered free cash flow and bridged to an equity value per share, with a sensitivity grid across discount rate and exit multiple.
DCF, EUR Mn2023E to 2027E
Line2023E2024E2025E2026E2027E
Total revenue12,411.6613,337.6114,332.6415,401.9016,550.92
Y/Y growth7.5%7.5%7.5%7.5%7.5%
EBITDA2,167.472,329.172,502.942,689.662,890.32
EBITDA margin17.5%17.5%17.5%17.5%17.5%
Less: D&A538.38578.54621.70668.08717.92
EBIT1,629.101,750.631,881.242,021.582,172.40
Less: income taxes(355.75)(382.29)(410.81)(441.45)(474.39)
NOPLAT1,273.351,368.351,470.431,580.131,698.01
Plus: D&A538.38578.54621.70668.08717.92
Less: capex759.74816.42877.33942.781,013.12
Less: incr. working capital104.07111.84120.18129.14138.78
Unlevered FCF947.911,018.631,094.621,176.281,264.04
Discount factor0.9530.8380.7360.6470.568
PV of FCF903.35853.24805.63760.67718.22
Total discounted FCFF4,041.12
PV of terminal value8,211.37
Enterprise value12,252.49
Plus: surplus cash1,666.00
Less: debt3,234.00
Equity value10,684.49
Value per share, EUR143.46
WACC 13.8%, terminal growth 4.7%.
Value per share sensitivity, EURWACC × exit multiple
WACC4.0x4.5x5.0x5.5x6.0x
11.8%130.7142.7154.6166.5178.4
12.8%126.0137.4148.9160.4171.8
13.8%121.4132.4143.5154.5165.5
14.8%117.0127.7138.3148.9159.5
15.8%112.9123.1133.3143.5153.7
Base case at 13.8% WACC and a 5.0x exit multiple. ABI Nexa research, from company filings.
Segment build
Forecast by geography, each on its own path
Apple's revenue is built from its geographic segments, each growing at its own rate, so a fast region like Japan and a mature one like Americas are not forced onto one number.
Geographic segment buildbase $M, then growth
SegmentBaseFY26EFY27EFY28EFY29EFY30E
Americas178.4B9.5%8.9%8.2%7.6%6.9%
Europe111.0B7.4%6.9%6.5%6.1%5.6%
Greater China64.4B6.2%5.8%5.5%5.2%4.9%
Japan28.7B20.0%18.3%16.6%14.9%13.2%
Rest of Asia Pacific33.7B4.9%4.7%4.5%4.4%4.2%
Consolidated revenue416.2B452.8B490.4B528.6B567.1B605.2B
Operating margin held at 30.4%. Apple 10-K, accession 0000320193-25-000073.
What you get

What lands on your desk.

A model already built

Open a name and a three-statement model, a segment build, a driver DCF and a football field are already there, 15+ years standardized.

Driver-based, not hard-coded

Revenue builds from the segments and KPIs the company reports, so a change flows through the model the way it flows through the business.

Forecast the way the sector works

Subscribers times ARPU, loan book and margin, pipeline rNPV for pharma, reserves NAV for energy, per the method the business demands.

Refreshed on the print

The model rolls to the latest filing on its own, so you react on the print, not the vendor lag.

Yours to change in Excel

Adjust the assumptions in your own workbook. It is a built model to argue with, not a locked output.

Every historical cell cited

Each figure names its filing, so the whole model is auditable end to end when someone senior asks.

In practice

How it changes the day.

01

Initiate in an afternoon

Open the name and the model is there: 15+ years standardized, a segment build, a driver DCF and a football field. Every historical cell names its filing.

0 wrong numbers on the audited sample
By hand today
Rebuild a three-statement model, segment build and valuation from a blank workbook before you can form a view.
Days per name.
02

React on the print

The model rolls to the latest filing on its own; change a vintage and the model, profile, screen and memo move together.

from the filing, not a vendor lag
By hand today
Re-key the quarter by hand when earnings drop, weekend gone before the call.
Every print.
03

A forecast that matches the business

The forecast is driven by the operating KPIs that move the business, per segment, where the company discloses them, and by the method the sector demands. Subscribers and ARPU, stores and sales density, loan book and margin; pipeline rNPV for pharma, reserves NAV for energy.

every driver cited
By hand today
Forecast every sector the same way, because the model only knows revenue growth and a margin.
04

Hand off a model that proves itself

Every historical cell names its filing; the whole model is auditable end to end.

By hand today
Hand off a model someone else has to trust blind.
What comes with the model.
Excel add-in. Refresh the model on the print, in place.Research Workspace. The whole file behind the model.Investment Memoranda. Turn the model into a cited write-up.Data API. The same facts, programmatic.
7,500+
pre-built models, US, India and foreign filers
15 years
of history, restatements kept
29.8M
facts, each one cited
0
wrong on the source-verified sample

See it on your own coverage.

Tell us the names and markets you follow and we will show you the desk on them.

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