Kensho is live · custom pricing · last verified 6 Nov 2026 · viability healthy
Kensho
S&P Global's AI engine, connecting LLMs and agents to vetted financial data through deterministic and adaptive retrieval.
If you already license S&P Global data and your agents need to reach it, Kensho is the shortest legitimate path: deterministic retrieval returns reproducible results, which is the part most LLM data plumbing can't promise, and Adaptive Retrieval now handles the messy open-ended questions. The RBC rollout to 8,000 bankers on Aiden at a reported 98% query accuracy is a stronger proof point than any benchmark, and the September 2026 Cohere North partnership plus MCP Apps inside Claude and ChatGPT widen where the data can land. If you have no S&P Global relationship, stop here — Bloomberg or a generic retrieval stack is the conversation, not Kensho.
Verdict generatedVerified 8d ago · liveness 86/100 · cite: rightaichoice.com/tools/kensho
- Financial institutions already licensing S&P Global data
- Enterprise AI developers building on vetted, auditable retrieval
- Analyst and research teams querying company profiles in natural language
- Compliance-heavy desks needing traceable answers
- Teams without an existing S&P Global data relationship
- Groups wanting a general-purpose AI assistant or consumer chat product
- Anyone needing coverage outside what S&P Global publishes
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Skip Kensho if your organisation doesn't already license S&P Global data — the retrieval layer, identifiers and 70-million-company coverage all assume that underlying relationship, so you'd be buying a connector to a database you can't access.
Coverage breadth is tied to which S&P Global datasets you're licensed for, so adding Capital IQ Professionals or Key Developments through the LLM-ready API can mean a separate dataset entitlement beyond the portal
Kensho is priced inside an S&P Global data relationship rather than as a standalone subscription, so it competes against the cost of building retrieval plumbing yourself or bolting a generic vector store onto licensed data. For a bank or asset manager already paying for Capital IQ, the incremental spend buys auditability; for a small team without that licence, the whole stack — data plus retrieval — is a different order of magnitude than a general-purpose AI tool.
In short
Kensho — S&P Global's AI engine, connecting LLMs and agents to vetted financial data through deterministic and adaptive retrieval. Best for Financial institutions already licensing S&P Global data, Enterprise AI developers building on vetted, auditable retrieval, Analyst and research teams querying company profiles in natural language. Pricing is on request (custom quotes).
No head-to-head comparison for Kensho yet — the alternatives below are the closest matches we list.
What is Kensho?
Kensho — S&P Global's AI engine, connecting LLMs and agents to vetted financial data through deterministic and adaptive retrieval. Best for Financial institutions already licensing S&P Global data, Enterprise AI developers building on vetted, auditable retrieval, Analyst and research teams querying company profiles in natural language. Pricing is on request (custom quotes).
Kensho is S&P Global's AI engine, built to get vetted financial data into large language models, agents, and AI applications where a plausible-sounding answer isn't good enough. The S&P Global AI Data Portal sits at the centre and exposes that data two ways: deterministic retrieval for exact, reproducible queries, and Adaptive Retrieval — launched in 2026 — for open-ended, underspecified questions in autonomous multi-agent systems. That pairing now covers both ends of the retrieval spectrum. Underneath sit the core AI building blocks. Extract turns unstructured financial PDFs into machine-readable data and interprets complex page layouts. Link matches messy company records to S&P Global IDs and global identifiers across 70 million public and private companies in S&P Capital IQ Pro and BECRS, with a link score quantifying match confidence. NERD extracts entities from unstructured text, Scribe transcribes earnings calls in real time, and Find — whose dataset research was accepted at ACL 2026 — flags inconsistencies inside documents, with top models surfacing over 60% of them, including errors the original authors missed. The delivery layer keeps widening. The LLM-ready API added S&P Capital IQ Professionals and Key Developments datasets in September 2026. MCP Apps (beta) render S&P Global charts and tables inside Claude and ChatGPT, a Cohere partnership puts the same data into the North agentic platform for research, analysis and reporting, and RBC Capital Markets extended the pattern to 8,000 bankers on its Aiden platform at a reported 98% query accuracy. Positioning is enterprise-first. Kensho is not a general-purpose assistant or a data marketplace for teams outside the S&P Global ecosystem — it is the retrieval and enrichment layer for institutions that already run on that data and now need it reaching agents without losing auditability.
Key features
- S&P Global AI Data Portal connects LLMs, agents and AI apps to financial data
- Deterministic retrieval for exact, reproducible and auditable AI queries
- Adaptive Retrieval for open-ended, underspecified questions in multi-agent systems
- LLM-ready API delivering S&P Capital IQ Professionals and Key Developments datasets
- Kensho Extract converts unstructured financial PDFs into machine-readable data
- Extract interprets complex financial page layouts for clean downstream inputs
- Kensho Link matches company data to S&P Global IDs and global identifiers
- Link score quantifies match strength on messy or incomplete company records
- Coverage of 70 million public and private companies via S&P Capital IQ Pro and BECRS
- NERD extracts companies, people and locations from unstructured text
- Scribe transcribes earnings calls in real time
- Find dataset detects inconsistencies within documents, including errors authors missed
- MCP Apps (beta) render S&P Global charts and tables inside Claude
- MCP Apps (beta) render S&P Global charts and tables inside ChatGPT
- S&P Global data on Cohere North for agentic research, analysis and reporting
Behind the verdict
Kensho's value isn't that it can call a model — plenty of tools do that. It's that the retrieval is grounded in a licensed dataset with lineage, and the design acknowledges a distinction most AI data plumbing glosses over: deterministic retrieval (exact, reproducible, auditable) versus adaptive retrieval (open-ended, underspecified, aimed at multi-agent autonomy). Compliance-heavy desks care about the first; agent builders need the second. Kensho now ships both under the S&P Global AI Data Portal, with Adaptive Retrieval added in 2026. The core AI capabilities are the underrated half. Extract handles complex financial page layouts rather than treating every PDF as flat text. Link does entity resolution across 70 million public and private companies in S&P Capital IQ Pro and BECRS, and returns a link score so you can set your own confidence threshold rather than trusting a silent match — the practical way to de-duplicate a CRM. Find, with ACL 2026-accepted dataset research behind it, targets inconsistencies within documents and reports top models catching over 60% of them, including errors the authors missed; read that as a research result, not a guarantee for your corpus. NERD and Scribe round out the enrichment and real-time transcription layer. The weak spots are real. MCP Apps is labelled beta in Kensho's own material, so treat chart and table interaction inside Claude and ChatGPT as emerging rather than load-bearing. Scribe is scoped to earnings calls and investor meetings, not general audio. Coverage is bounded by what S&P Global publishes — if your question is about private internal corpora at scale or non-financial data, the enrichment tooling is aimed elsewhere. And the public site documents the capabilities far more thoroughly than the commercial terms, so cost is something you evaluate inside an existing S&P Global relationship. Where it fits: banks, asset managers, and research teams already on Capital IQ or BECRS that need agent workflows reading the same data with an audit trail. Where it doesn't: startups wanting a general assistant, or teams without the underlying licence.
Models under the hood
as of 2026-11-08
Limitations
- Kensho is deliberately narrow: finance-specific data infrastructure, not a general AI platform.
- Teams without an S&P Global relationship are not the audience, and non-financial or small-scale projects will find it overkill.
- MCP Apps is labelled beta in Kensho's own material, so expect limited functionality or reliability on charts and tables returned inside Claude and ChatGPT.
- Scribe targets earnings calls and investor meetings rather than general audio.
- Find's headline result — top models surfacing over 60% of document inconsistencies — comes from Kensho's ACL 2026 dataset research, not a guarantee for your corpus.
- Coverage is bounded by what S&P Global publishes.
as of 2026-10-19
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Is Kensho still active?
Kensho is live · custom pricing · last verified 6 Nov 2026 · viability healthy.
Viability score
How well maintained and how widely used is Kensho? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What's new in Kensho
Checked 5 days agoAcross the latest 5 updates: 1 feature update, 1 launch and 3 news mentions.
Kensho LLM-ready API adds Key Developments and Professionals datasets
The LLM-ready API expands deterministic retrieval coverage with S&P Capital IQ Professionals data and Key Developments.
S&P Global partners with Cohere to bring data into North platform
Financial data is now accessible inside Cohere's secure agentic AI platform North for research, analysis and reporting.
Kensho FIND dataset research accepted at ACL 2026
Kensho research shows top models surface over 60% of document inconsistencies, including errors authors missed.
S&P Global launches Adaptive Retrieval for AI and agentic workflows
Adaptive Retrieval joins Deterministic retrieval under the S&P Global AI Data Portal, targeting autonomous multi-agent systems.
RBC Capital Markets scales S&P Global and Kensho AI to 8,000 bankers
RBC integrated S&P Global data into its Aiden platform with Kensho Labs, scaling to 8,000 employees at 98% query accuracy.
What do users say about Kensho?
What people actually say about Kensho — is it worth it?
We scanned public community sources for Kensho on Oct 13, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 4 of the posts we fetched could be positively tied to Kensho. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
How we verified this
Every listed fact about Kensho — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 6 Nov 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified Kensho 26 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed SSL certificate
- — changed pricing fit, switching out, who it suits, switching in, use cases, features, description, who should skip it, hidden costs, setup time, limitations, summary, our verdict
- — changed description, summary, who should skip it, who it suits, features, our verdict
- — changed pricing page
- — changed switching out, who it suits, description, our verdict, features, hidden costs, limitations, switching in, pricing fit, setup time, who should skip it, summary, use cases
- — changed our verdict, who it suits, summary, who should skip it, features, description
Showing the 6 most recent of 26 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Kensho cost in 2026?
Kensho: Pricing is on request (custom quotes). Pricing last verified 6 Nov 2026.
Where the pricing makes sense
The company stage and team size where Kensho's pricing actually pencils out — and where peers do it cheaper.
Kensho is priced inside an S&P Global data relationship rather than as a standalone subscription, so it competes against the cost of building retrieval plumbing yourself or bolting a generic vector store onto licensed data. For a bank or asset manager already paying for Capital IQ, the incremental spend buys auditability; for a small team without that licence, the whole stack — data plus retrieval — is a different order of magnitude than a general-purpose AI tool.
Has Kensho's pricing changed?
No plan price for Kensho has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Kensho?
Pick Kensho if you are Financial institutions already licensing S&P Global data, Enterprise AI developers building on vetted, auditable retrieval, Analyst and research teams querying company profiles in natural language, Compliance-heavy desks needing traceable answers.
Look elsewhere if you are Teams without an existing S&P Global data relationship, Groups wanting a general-purpose AI assistant or consumer chat product, Anyone needing coverage outside what S&P Global publishes, Projects applying enrichment to non-financial internal corpora at scale.
Skip it if Skip Kensho if your organisation doesn't already license S&P Global data — the retrieval layer, identifiers and 70-million-company coverage all assume that underlying relationship, so you'd be buying a connector to a database you can't access.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Kensho actually fits — and what changes day-one when you adopt it.
You're building an internal agent that answers questions about company fundamentals and must be reproducible for compliance review. You point it at deterministic retrieval in the S&P Global AI Data Portal and pull Capital IQ Professionals data through the LLM-ready API.
Outcome: Every answer traces back to a specific licensed record, and re-running the same query returns the same result — the audit trail compliance asks for.
Your CRM holds hundreds of thousands of inconsistently spelled company records with duplicate entries. You run them through Kensho Link, which matches against S&P Global IDs across 70 million public and private companies and returns a link score per record.
Outcome: You set a confidence threshold, auto-accept high-score matches and queue the rest for review, cutting duplicate and mismatched accounts without manual lookup.
You want to interrogate filings and earnings transcripts without leaving Claude. Through MCP Apps (beta) you pull S&P Global charts and tables into the conversation, and use Scribe to transcribe the earnings call you're covering.
Outcome: Charts and tables render inline from trusted data rather than model recall, and the transcript is available in real time — though you should expect beta-level rough edges on the MCP surface.
Use cases
- Query S&P Global data inside Claude or ChatGPT and interact with returned charts and tables via MCP Apps.
- Match millions of messy CRM records to S&P Global IDs with Kensho Link and surface duplicates.
- Convert financial PDFs and filings into machine-readable data with Kensho Extract.
- Link companies, people and locations in news or research text to S&P Global identifiers with NERD.
- Transcribe earnings calls and investor meetings in real time with Scribe.
- Detect inconsistencies inside financial documents using the Find dataset.
- Annotate thousands of words in seconds to build enriched, S&P Global-backed JSON training data.
- Run agentic financial workflows on Cohere North using S&P Global data.
Setup time & first value
How long it actually takes to get something useful out of Kensho — broken out by persona, not the marketing-page minute.
For a developer already holding S&P Global credentials, pulling the LLM-ready API into an existing agent is an afternoon's work to a first successful query. Linking a real CRM extract with Kensho Link takes longer — plan a week to calibrate the link-score threshold against a sample before running millions of entities. Teams without an existing data relationship should expect procurement, not
Switching to or from Kensho
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a custom vector-store RAG pipeline: replace the retrieval layer with the S&P Global AI Data Portal's deterministic endpoint so answers resolve to licensed records rather than embedded chunks.
- →From manual analyst lookup in Capital IQ: route recurring company-profile and Key Developments queries through the LLM-ready API inside your existing assistant.
- →From a generic entity-resolution vendor: run a sample of your records through Kensho Link and compare confidence scores before switching.
- ↗To a generic retrieval stack: you keep the documents but lose S&P Global identifier resolution and the link score, so entity matching reverts to in-house work.
- ↗To Bloomberg or another data vendor's AI layer: the workflow pattern carries over, but identifiers, coverage and dataset entitlements do not.
Resources & guides
- Resourcekensho.com
Enterprise AI Solutions for Finance | Deterministic and Adaptive Data Retrieval
Explore Kensho’s suite of AI solutions. From LLM-ready APIs and the Kensho Grounding Agent to core ML capabilities, we provide the infrastructure to power trusted, agentic AI in global business and financial services.
- Resourcekensho.com
Careers at Kensho | Join the Team Shaping Financial AI — Kensho | S&P Global’s AI Engine | Enterprise Data Retrieval
Build the future of agentic AI and machine learning. Explore open roles in engineering, research, and data science at Kensho’s Cambridge and NYC hubs and around the globe.
- Resourcekensho.com
Kensho News | Latest Updates in Financial AI & ML Innovation — Kensho | S&P Global’s AI Engine | Enterprise Data Retrieval
Stay informed on Kensho’s latest product launches, research breakthroughs, and partnerships within the S&P Global and AI ecosystems.
Tutorials & Learning
YouTube returned 6 videos for “Kensho”, and we withheld 6: 6 could not be judged, because “Kensho” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Kensho.
Official links
What are the best Kensho alternatives?
The closest alternatives to Kensho we list are OpenBB, Kavout and MarketAlerts.ai. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| OpenBB | Freemium | Pricing not published | — |
| Kavout | Freemium | Pricing not published | — |
| MarketAlerts.ai | Contact Sales | Custom pricing | — |
Alternatives to Kensho
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MarketAlerts.ai
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Tools that pair well with Kensho
Common stack mates teams adopt alongside Kensho, with the specific reason each pairing earns its keep.
OpenBB
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Kavout
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MarketAlerts.ai
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Frequently asked questions
Best-of guides
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