S&P Capital IQ Alternatives in 2026

For AI research built on company filings and your firm’s own data, the best S&P Capital IQ alternative is Kepler. We assemble statements from each filing’s XBRL with every cell cited to the line, compute comps in code so every multiple traces to its line items on each filer’s own adjusted EBITDA, and our engineers build your firm’s ontology so your definitions, coverage lists and internal models shape every answer.

S&P Global put Capital IQ under strategic review on October 27, 2026, and teams heading into a renewal are asking what else is out there. This page covers what S&P announced, why firms look elsewhere, and the alternatives by job: full terminals, private-markets data, lower-cost research platforms, model-ready data, and AI built around your firm.

We build Kepler, so it’s first and labeled. Facts about other vendors come from their websites, press releases and public reporting as of November 2026, linked inline, and prices appear only where a vendor publishes them or a reputable source reports them.

What S&P Global announced

In its third-quarter earnings release, S&P Global said it “has initiated a strategic review of alternatives, including potential separation, for Capital IQ and associated data businesses, which constitute the majority of Kensho Data & Platforms within Market Intelligence.” The company expects to keep RatingsDirect, RatingsXpress and Enterprise Solutions, and said the exact perimeter is still under review. Its case for the review: “separate ownership could provide dedicated investment and focus” for the businesses involved.

The release also says there is no specific timeframe and no assurance of any transaction, and S&P’s 2026 guidance assumes Market Intelligence stays as it is for the full year. For a subscriber, nothing changes on day one. What changes is the planning horizon: a multi-year renewal signed now could run past a change of owner, roadmap or bundle.

Why firms look for Capital IQ alternatives

• Ownership uncertainty. A review that could end in a separation is a reason to test alternatives before signing a long term.
• Standardized numbers that don’t match the filing. Database templates map each company’s lines into a standard format, and the result can differ from what the company reported and from the firm’s own adjustments.
• The firm’s own definitions. Every desk adjusts EBITDA, free cash flow and segment mappings its own way, and those rules live in each analyst’s spreadsheet rather than in the platform.
• Excel dependence. Models wired to vendor formulas depend on that vendor’s plug-in, identifiers and entitlements staying put, and outside Excel some users find the platform slow. What users say: “Not well suited for looking for data given how slow S&P CIQ Pro is relative to Bloomberg,” a TrustRadius reviewer in finance and accounting wrote in January 2025.
• AI that shows its work. Analysts want answers that open the exact line in the filing and the arithmetic behind every derived number.

Capital IQ alternatives at a glance

Tool	Best for	Core content	Your firm’s data	Where numbers come from
Kepler	AI research on filings and your firm’s own data	26M+ SEC filings with XBRL, 40M+ IR documents and transcripts, market data, news	Your firm’s ontology, every document read in full	Computed by code, cited to page, line or cell
FactSet	A full workstation with data in your AI tools	Fundamentals, estimates, ownership, M&A, pricing	Through your AI assistant	Standardized datasets
Bloomberg Terminal	Real-time markets, news and analytics	Bloomberg data, news, research from 800+ providers	Chats, Worksheets, Bloomberg Drive	Bloomberg data with attribution
LSEG Workspace	Multi-asset data, StarMine and MarketPsych analytics	LSEG data and news	Through LSEG’s MCP server and Microsoft 365	Licensed datasets with citations
PitchBook	Private companies, funds and deals	Private-market data	No	PitchBook research data
Koyfin	Fundamentals and charting at a published price	80,000+ companies, filings, transcripts	Portfolios and custom formulas	Standardized datasets
Daloopa	Source-linked historicals for your own models	6,000+ companies, up to 14 years	Your own Excel models	Extracted, each point linked to its document
Fiscal.ai	Standardized and as-reported financials by API	Segments and KPIs for the largest 2,300 companies	No	Data with an optional source-image add-on

The best Capital IQ alternatives

1. Kepler (our pick)

We build Kepler.

Best for: hedge funds, equity research teams and investment banks whose Capital IQ use centers on public-company fundamentals, screens and comps, and who want those numbers provable and on the firm’s own definitions.

A terminal answers “what does the database say?” The question that reaches a PM or an investment committee is narrower and harder: what did the company actually report, how does it compare on our definition, and can you show me? A standardized database answers the first part fast. The rest still happens in a spreadsheet, by hand, with every figure checked against the filing.

We built Kepler to do the rest. Our engineers built this layer before at Palantir, and on site with your team they build your firm’s ontology: every company, segment, peer set and holding resolves to one record, and your adjusted EBITDA, your organic growth and your calendarization rules each carry one definition. Public data is ready on day one: 26M+ SEC filings across 20+ form types with full text and XBRL, 40M+ IR documents and earnings call transcripts, market data and news, for 14,000+ companies in 120+ countries and 30+ languages. Extraction models we train read every page at ingest, including the MD&A tables, footnotes and non-GAAP reconciliations where the useful numbers hide, and store each fact with its scale and unit beside its passage.

The engine does the arithmetic. Statements assemble from the filer’s own XBRL with no model in the path, as originally filed or as restated, and every comp, margin and multiple computes as code over cited inputs with the formula one click away. Each citation is checked against its source before you see it. A screen across thousands of companies returns every match, because every document was read before you asked. Results land in Excel with live formulas and cited inputs, or in PowerPoint, Word, Claude, ChatGPT and Slack.

Agents keep it current: they rerun your comps the morning a peer files, flag a guidance change with the quote, and send the PM what moved. Your playbooks (the comps sheet in house format, the earnings note your PM wants) are saved once and applied every time, and your engineers can build on the same data and engine through our API and MCP server.

Why it’s our pick for public-company research

• Comps you can defend: every multiple traces to its line items, on each filer’s own adjusted EBITDA or on yours.
• As filed or as restated: point-in-time history on any date, with recasts flagged. In our paper Reclassified to Conform, 194 of 200 companies reshaped a statement in ways XBRL tags can’t follow.
• Screens on what companies disclose, run across every filing and transcript, returning the complete set.
• Your firm’s ontology, so house definitions and coverage lists apply to every answer (how it works).
• Agents you can leave alone, acting as their owner and never steered by what they read.
• Kepler everywhere: Excel with live formulas, PowerPoint, Word, Claude, ChatGPT, Slack and the Kepler API.
• Your rules built in: one permission check on every read, every calculation logged with its lineage, SOC 2 Type II, our cloud or yours (security).

Questions teams bring to Kepler

• “Trading comps for US vertical software: EV/NTM revenue and EV/EBITDA on each filer’s own adjusted EBITDA, every multiple traced to its line items.”
• “Industrials in our coverage whose free cash flow conversion fell below 70% in each of the last three years, on our definition.”
• “When any company in this peer set files a 10-Q, refresh the comps sheet and tell me what changed.”

“Kepler’s numbers match the filings. My team stopped re-checking every figure before it goes to a client.” (Vice President, Global Investment Bank)

Not the right fit if: your desk needs one terminal for real-time prices, bond and credit analytics and deal databases under a single subscription.

Run a comps set you already know at app.kepler.ai, or book a demo on your coverage list. Our guide to building trading comps with AI walks through the method.

2. FactSet

Best for: firms that want a full workstation and its data inside the AI tools they already use.

FactSet is the closest like-for-like replacement: fundamentals, estimates, ownership, M&A, pricing and its Excel tools in one workstation. Its MCP server brings that data to AI assistants: a Claude connector was added in February 2026 and a Gemini Enterprise integration went live in August.

What users say: “I do find the financial statement data such as cash flow, capex can sometimes be incorrect for international companies,” a VP of product wrote on Capterra in November 2025.

Trade-offs: contract pricing, and switching means re-pointing every Excel formula. Vendr reports a median FactSet contract of $25,160 a year.

3. Bloomberg Terminal

Best for: teams whose day runs on real-time markets, news and messaging.

The Terminal leads on live prices, fixed income and news. Its conversational AI, ASKB, opened in beta in February 2026 and became generally available on October 15. Its agents draw on Bloomberg data, news and research from more than 800 providers, return the BQL code behind any data analysis for use in Excel or BQuant, and can now read a client’s own chats, Worksheets and Bloomberg Drive files.

What users say: “FA function lacks Non-GAAP adjustments for the non-GAAP numbers provided by companies,” a financial analyst wrote on TrustRadius in November 2025.

Trade-offs: cost. NeuGroup reported a single Terminal at $31,980 a year from 2025 ($28,320 per Terminal for multi-Terminal clients). See AlphaSense vs Bloomberg ASKB.

4. LSEG Workspace

Best for: multi-asset teams that want LSEG data, StarMine analytics and AI answers with citations.

LSEG Workspace, the successor to Refinitiv Eikon, combines LSEG data and news with proprietary analytics such as StarMine and MarketPsych, plus AI features LSEG describes as auditable and repeatable, with citations back to the source. Its MCP server delivers data licensed through Workspace to AI assistants and agent platforms with existing entitlements respected, and Workspace also runs inside Microsoft Teams.

What users say: “My boss is done tired of the LSEG eikon/workspace product and wants to move to a different provider,” a hedge fund analyst wrote on Wall Street Oasis in January 2025.

Trade-offs: priced by quote, and strongest where LSEG’s own content is; check depth for small caps and the KPIs you track.

5. PitchBook

Best for: teams whose Capital IQ use is mainly private companies, funds, investors and deals.

PitchBook, owned by Morningstar, is the private-markets specialist. Navigator, its generative AI assistant launched in November 2025, answers natural-language questions across PitchBook data, and subscribers can reach the same data from ChatGPT and Claude through connectors.

What users say: “The Pitchbook research team does not give specific answers about where they source their information,” a strategy analyst wrote on Capterra in May 2026.

Trade-offs: a private-markets dataset first. Public-company fundamentals and comps are thinner than a full terminal’s.

6. Koyfin

Best for: smaller teams and independent analysts who want fundamentals, screens and charts at a published price.

Koyfin publishes its prices: a free tier, Plus at $39 a month and Premium at $79 a month on annual billing, with advisor plans above that and team plans by quote. Plus includes 10 years of financials and estimates, unlimited screens and dashboards, filings, transcripts and news; Premium adds custom formulas and financial templates. Its coverage spans 80,000+ companies worldwide.

Trade-offs: a research terminal for one person or a small team. There’s no deployment on a firm’s documents or definitions, and enterprise data feeds are out of scope.

7. Daloopa

Best for: analysts who want source-linked historicals and KPIs flowing into their own Excel models.

Daloopa covers 6,000+ public companies with up to 14 years of history, each data point hyperlinked to its source. Its add-in refreshes models after a print, Scout builds and updates models in Excel, and its MCP connector reaches Claude, ChatGPT and Microsoft 365 Copilot. Daloopa keeps both the originally reported and the restated value when a company revises a figure (docs).

Trade-offs: historicals only: no consensus, credit or transactions, and prices aren’t published. See Daloopa alternatives and Kepler vs Daloopa.

8. Fiscal.ai

Best for: teams building their own tools on a financial data API.

Fiscal.ai, formerly FinChat, sells a research terminal and an API with standardized and as-reported financials (20+ years annual, 40+ quarters), segments and KPIs for the largest 2,300 companies by market capitalization, estimates, ownership, transcripts and fund letters. A Sourcing to Filing add-on attaches an image and PDF of the source table to each figure, and its MCP server works with Claude, ChatGPT, Gemini Enterprise and Microsoft 365 Copilot.

Trade-offs: KPI depth stops at the largest 2,300 companies, and coverage of some datasets is limited to the US and Canada. See Fiscal.ai alternatives.

What Capital IQ does well

Capital IQ Pro is one of the broadest platforms on the market: fundamentals, estimates, screening, M&A and capital markets data, credit research and an Excel plug-in in one subscription. Its October 2026 update added ChatIQ Spreadsheets, an Excel modeling assistant that works with refreshable Capital IQ Pro formulas, plus point-in-time trading comparables and a new DCF tool.

Kepler vs Capital IQ

	Kepler	S&P Capital IQ Pro
Built around	Your firm: its ontology, documents and definitions	S&P’s standardized datasets
Where each number comes from	Pulled from the filing and computed by code	S&P’s database, in S&P’s templates
What a citation opens	The exact page, line or cell, with formula and inputs	Document citations in ChatIQ answers
Your firm’s definitions	Built into your ontology, applied to every company	Kept in your own spreadsheets
As filed vs as restated	Either, on any date, with recasts flagged	Point-in-time comps (October 2026 update)
Screens on disclosures	Every filing and transcript read in full, complete results	Screens on database fields, plus screening in ChatIQ
Your own documents	Notes, models, CRM and data rooms in your ontology	Built around S&P content
Work that runs on its own	Agents on schedules and filings, acting as their owner	Alerts and refreshable formulas
Where it works	App, Excel, PowerPoint, Word, Claude, ChatGPT, Slack, API	Capital IQ Pro, Excel plug-in, connectors to AI tools

How to choose

Start with what you use Capital IQ for:

• Real-time markets, fixed income and news: Bloomberg or LSEG Workspace.
• A like-for-like workstation with M&A and ownership data: FactSet.
• Private companies, funds and deals: PitchBook.
• Fundamentals and charts at a published price: Koyfin.
• Historicals flowing into your own models: Daloopa, or Fiscal.ai’s API.
• Public-company research, comps and screens on your firm’s definitions, with every number provable: Kepler.

Then, before your renewal:

1. Find your term and notice dates, and how long a new contract would run past any change of ownership.
2. List your Excel dependencies. Count the models wired to Capital IQ formulas and decide which ones need live data and which only need historicals.
3. Test on a comps set you already know. Rebuild it in each tool, click every multiple back to its line items, and ask the same question twice. Our guide to checking AI numbers has the full routine, and Daloopa alternatives covers more data suppliers.

Build a comps set at app.kepler.ai, or book a demo on your own coverage list and definitions.

Frequently asked questions

What is the best alternative to S&P Capital IQ?

For AI research built on company filings and your firm's own data, our pick is Kepler. Statements come straight from each filing's XBRL with every cell cited, comps compute in code so every multiple traces to its line items on each filer's own adjusted EBITDA, and our engineers build your firm's ontology so house definitions apply to every answer. It fits teams whose Capital IQ work centers on public-company fundamentals, screens and comps.

What did S&P Global announce about Capital IQ in October 2026?

On October 27, 2026, alongside its third-quarter results, S&P Global said it had begun a strategic review of alternatives, including a potential separation, for Capital IQ and associated data businesses, which make up most of Kensho Data & Platforms inside Market Intelligence. It expects to keep RatingsDirect, RatingsXpress and Enterprise Solutions. S&P set no timeframe and said the review may not lead to any transaction.

Should we change our Capital IQ contract because of the review?

Nothing changes for subscribers on announcement day, and S&P has said there's no timeframe. The practical step is to know your renewal date and term length, list the workflows that depend on Capital IQ formulas in Excel, and test alternatives on live work before the renewal conversation, so a change of ownership never forces a rushed decision.

Who are S&P Capital IQ's main competitors?

The full terminals are FactSet, the Bloomberg Terminal and LSEG Workspace. PitchBook competes on private companies, funds and deals. Koyfin offers fundamentals and charting at published prices. Daloopa and Fiscal.ai supply model-ready fundamentals and KPIs. Kepler competes on AI research built around the firm itself, with every number computed in code and cited to the line.

Is there a cheaper alternative to Capital IQ?

Koyfin publishes its prices: a free tier, Plus at $39 a month and Premium at $79 a month on annual billing, with 10 years of financials and estimates on Plus. Its coverage spans 80,000+ companies. FactSet, Bloomberg and LSEG are priced by quote; Vendr reports a median FactSet contract of $25,160 a year, and a single Bloomberg Terminal was reported at $31,980 a year.