Capital Markets & Research AI
C

Cohesion

Cohesion sells a team of monitoring agents to fundamental equity investors, tracking the companies an analyst covers across earnings calls, investor presentations, regulatory filings, news, podcasts and social feeds, filtering out noise and reporting the developments that bear on an existing investment thesis. The pitch is aimed at the manual half of an analyst's week, the hours spent querying platforms and reading through sources that older research systems do not capture at all, and the company positions the product as an agentic teammate rather than a search tool.

It was founded in 2026 in New York by three people whose backgrounds sit either side of the problem, a hedge fund analyst covering software, an engineer from a cloud provider's security organization, and a builder of investor facing artificial intelligence at a large asset manager. It reports being live with more than ten long and short and long only fundamental equity funds managing a combined $10 billion or more, and offers a free trial in which a prospective fund submits a list of tickers ahead of earnings season.

Last VerifiedAugust 17, 2026
Compare Cohesion with other vendors
Founded
2026
Headquarters
New York, New York, United States
Categories
capital-markets-ai, wealth-and-advisory
Assessment

Capability Axes

Capability grades

15 of 15 axes rated · 1 graded A or B

AI Capability
AI Centrality
AA on AI CentralityThe artificial intelligence is the product. Remove the models and there is nothing left to sell.
Vendor Published

Cohesion sells the agents' work and nothing underneath it: continuous monitoring of a coverage list across sources that have no structured feed, podcasts and social posts among them, with a judgment about which developments matter to a stated thesis. Remove the models and nothing remains but a list of tickers. The company's own framing is that analysts spend hours a week doing this by hand and the agents now do it for them.

Autonomy and Oversight Model
CC on Autonomy and Oversight ModelAutonomy is claimed and oversight is asserted without a mechanism, or full automation is presented as the entire disclosure. Human in the loop appears as a phrase rather than a described control.
Vendor Published

Autonomy is the selling point and is stated as such, agents that monitor and generate differentiated insights without the analyst driving each step. The consequence is contained because the output is research rather than an executed decision, and a portfolio manager still sizes the position. What is missing is any description of what the analyst sees to check the work, whether an insight carries its source, or how a claim the agent got wrong is caught before it enters a thesis.

Model Risk Management and Transparency
CC on Model Risk Management and TransparencyTransparency is claimed in general terms with no mechanism a model validator could interrogate.
Vendor Published

A monitoring product has two failure modes and neither is measured publicly. The miss is a material development the agents did not surface, which is invisible to the client by definition, and the false signal is an insight drawn from a mis read transcript or a low quality post. No precision or recall figure, no grounding or citation guarantee, no evaluation method and no human review step is published. For a product whose output feeds position sizing, the missed event is the more consequential of the two and the harder to detect.

Operational and Outcome Evidence
CC on Operational and Outcome EvidenceUnnamed case studies, customer logos, or claims without numbers. Prestige is not measurement: the caliber of the client list describes the buyer rather than the product, and coverage statistics are not adoption statistics.
Vendor Published

The claim is more than ten long and short and long only funds live, with a combined $10 billion or more under management, self reported by a company founded this year with three employees. Assets under management behind a client list describe the caliber of the buyer, not the performance of the product. No fund is named, no accuracy or time saved figure is published, and no independent evaluation exists. That is a reasonable position for a company at this stage rather than a criticism of it.

AI Safety and Data Stewardship
CC on AI Safety and Data StewardshipGeneral assurances that do not answer the question this axis asks, which is whether one customer’s data trains models serving its competitors. Unbounded cross client learning stated with no boundary grades here too.
Vendor Published

The question that decides this product for an institutional buyer is whether one fund's coverage, questions or thesis notes inform what the system surfaces to another fund, since the customers compete directly for the same alpha. Nothing published addresses the boundary, offers an opt out or states whether client interactions train anything. Source licensing is equally unaddressed, which matters when the inputs include podcast audio and social platform content.

Regulatory and Compliance
GLBA and Data Privacy Posture
CC on GLBA and Data Privacy PostureA standard privacy policy that covers the website rather than the service, or silence on a product that touches limited consumer data.
Vendor Published

Consumer data exposure is absent, since the material is public company information. The sensitive asset is the client's own coverage list, because what a fund is watching and which theses it is tracking is itself signal. Nothing published describes how that is segregated, retained or protected, and there is no public privacy or confidentiality statement.

Security Certifications and Trust Center
CC on Security Certifications and Trust CenterA single footer line, or certifications asserted without being enumerated, which is weaker than naming them because it invites an assumption a buyer cannot check.
Vendor Published

There is no public certification, attestation or trust page. One founder's background is in a major cloud provider's security organization, which is a reason to expect competence and is not the same as a control a buyer can verify. At three employees no attestation would be expected yet, and institutional vendor review will ask for one before long.

Regulatory Status and Licensure
CC on Regulatory Status and LicensureThe regulatory position is unstated. Most vendors in this index are technology suppliers and being unlicensed is the correct posture, so this grade records silence about the posture, not a missing license.
Vendor Published

No licence is required to sell research tooling and none is claimed, which is the correct posture. Two regulated edges go unaddressed. Systems monitoring non traditional sources for signal on covered companies sit near the handling of material non public information, and generated research delivered into an investment process may fall inside a firm's supervised records and research policies. Neither appears in any public material.

AI Governance and Bias Disclosure
CC on AI Governance and Bias DisclosureResponsible artificial intelligence committed to in policy language with no evaluation behind it, on a product whose bias surface is modest.
Vendor Published

The relevant exposure is source selection rather than protected class fairness. An agent that ranks podcasts, social posts and press by apparent relevance inherits whichever voices are loudest and most indexed, which systematically favours widely covered large capitalisation names and English language sources, and thinly covered or non English issuers are exactly where an information edge is supposed to live. Nothing published describes source weighting, coverage limits by language or market, or how the system handles a company nobody is talking about.

AI Liability and Recourse
CC on AI Liability and RecourseMechanisms that enable challenge, such as audit trails and source traceability, with nothing standing behind the output and no route for the person affected.
Vendor Published

The loss from a missed disclosure lands entirely on the fund. No warranty, service level, correction process or allocation of responsibility appears anywhere, and nothing published describes what happens when the agents miss something that moves a position or surface an insight that turns out to be wrong. Research vendors usually leave that risk with the client, and it matters because the output is used in decisions with money attached.

Integration and Deployment
Model Supply Chain Disclosure
CC on Model Supply Chain DisclosureThe architecture is described and no provider is named.
Vendor Published

Nothing names a model, a provider, an infrastructure dependency or a data source agreement. A three person company shipping agentic monitoring in 2026 is almost certainly running on third party foundation models, so the practical question for a buyer is which ones, what happens on deprecation, and whether client coverage data crosses into a provider's environment. None of that is answerable from public material.

Core Systems and Integration Depth
CC on Core Systems and Integration DepthIntegration claimed through standards or connectors with no system named and nothing to verify.
Vendor Published

Nothing published names an integration. No order or portfolio management system appears, and neither does a research management platform, a market data provider or a note taking or collaboration tool. The trial is described as a ticker list sent to the vendor rather than a connection made to a client system. For a product meant to sit inside an analyst's daily workflow, that is the gap that matters as the product matures.

Deployment Model and Data Residency
CC on Deployment Model and Data ResidencyCloud only with nothing stated, which is the category norm.
Vendor Published

Delivery is a hosted platform and nothing further is stated. No region, tenancy model, private deployment option or residency commitment is published, which is a live question for any fund with data handling obligations attached to its own coverage information.

Commercial
Commercial Transparency
CC on Commercial TransparencyNo price is published and engagement runs through a demo form, which is the norm in this index.
Vendor Published

No pricing is published. The trial offer is concrete: a prospective fund sends twenty tickers and gets coverage through an earnings season. That tells a buyer the unit of consumption is the covered name, even though no number is put against it. It is still well short of a rate.

Institution and Segment Coverage
CC on Institution and Segment CoverageSegments claimed broadly, banks, fintechs, credit unions, without evidence any of them has its own maintained surface.
Vendor Published

Deliberately narrow, and the narrowness is the strategy. The buyer is the fundamental equity fund, long and short or long only, and the product is built around how a covering analyst works rather than around an institution's data estate. Nothing indicates coverage of credit, macro, private markets, or the sell side, and no geography beyond the domestic listed market is described.

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The index publishes no overall score or ranking. See what we assess and the methodology.

Commercial

Pricing

Vendor-published figures are labeled as such. Figures labeled “Estimated” are derived from third-party sources and have not been confirmed by the vendor.

No pricing data has been verified for this vendor. Pricing information will be published here once confirmed through vendor disclosure or third-party estimation.

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AI FinTech Index

The AI FinTech Index is an independent index that tracks changes to AI vendors in financial services. It holds 610 vendors across banking, lending, insurance, wealth, capital markets and financial crime compliance, each graded on the same 15 capability axes from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
October 20, 2026
The AI FinTech Index is an editorial reference, not a regulatory body. Vendor data is verified against published sources and public regulatory filings. Figures labeled “Estimated” have not been confirmed by the vendor. See the Methodology page for evaluation standards and limitations.
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