Capital Markets & Research AI
E

Endex

Endex is a New York company building an AI agent that lives inside Microsoft Excel rather than in a separate platform, on the reasoning that Excel remains the working environment of investment banking, private equity and corporate finance. The agent retrieves, synthesises and reasons over financial data drawn from a firm's own internal files, public disclosures including securities filings, and licensed sources, unifying them into one searchable plane.

It builds three statement models and discounted cash flow valuations, extracts from documents, reconciles disagreeing sources, cross checks figures to surface discrepancies and flag restatements buried in footnotes, and can deliver output as an Excel model, a document, a slide deck or an email. Two oversight features are central to the product: integrated citations attributing every output to its underlying source, and workflow tracing that maintains labelled cell references so a user can see which cells the agent produced.

Buyers are named by category rather than by firm and span investment banks, private equity managers above 100 billion dollars in assets, global multi strategy hedge funds, Fortune 500 finance teams and listed real estate developers. Funding stands at roughly 14 million dollars, with the OpenAI Startup Fund among the backers.

Last VerifiedAugust 21, 2026
Compare Endex with other vendors
Founded
Headquarters
New York, New York, United States
Website
endex.ai
Categories
capital-markets-ai
Assessment

Capability Axes

Capability grades

15 of 15 axes rated · 6 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

The models are the entire product. There is no workflow platform, data asset or system underneath that would survive their removal, because the surrounding environment belongs to Microsoft rather than to this vendor: strip the inference and what remains is an empty spreadsheet add in. The company's own framing makes the point, describing a deliberate decision not to build a competing platform but to place an agent inside the tool finance already uses. Assistant native at its clearest.

Autonomy and Oversight Model
BB on Autonomy and Oversight ModelA written commitment that the models work alongside human judgment, with real review surfaces, short of the full control structure: commonly the threshold at which the system stops or what happens after it is wrong.
Vendor Published

Two real oversight properties, both unusual. Every output carries integrated citations attributing it to an underlying source, and workflow tracing maintains labelled cell references so a user can see which cells the agent produced rather than discovering them later. That second one is the more valuable and it is specific to this setting: a spreadsheet is exactly where an unmarked machine edit would be hardest to detect and most damaging.

Held off A because the agent writes into a live financial model and no approval gate before those writes is published, no confidence threshold routes a case to a person, and nothing states what the agent will not do.

Model Risk Management and Transparency
BB on Model Risk Management and TransparencyReal transparency mechanisms are published, such as per alert explainability, confidence scoring or split testing, without the validation package or supervisory mapping behind them.
Vendor Published

Earned on provenance stated consistently rather than asserted once. Outputs carry attribution to underlying sources, conclusions can be traced back through labelled cell references, and the system actively cross checks sources against each other, surfacing discrepancies and flagging restatements disclosed in footnotes with targeted citations. Catching a restatement buried in a footnote and citing it is a checkable behaviour, not a claim about explainability.

Held off A because no accuracy rate, benchmark, evaluation methodology or drift policy is published, and the one accuracy statement located, that a model change simplified the pipeline without sacrificing accuracy, is an assertion with no figure behind it.

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

The C bar as located. Customer categories are stated but no institution is named, and the testimonials on the vendor's own site are attributed to an unnamed hedge fund portfolio manager. One quoted figure exists, a three statement model and valuation built in ten minutes, but it comes from an anonymous user rather than an identified firm. A model provider has published an account of this vendor's work, which is an independent party naming the relationship, but it evidences the model dependency rather than a customer outcome.

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 vendor publishes no statement on whether customer files, models or queries are used to train or improve any model, no retention terms and no tenancy or isolation position. Compliance and security are invoked as commitments without accompanying terms. A buyer can infer where inference happens from the named model provider, which is more than most, but inference location is not a stewardship commitment.

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

The vendor publishes no processing terms, retention schedule, sub processor list or privacy commitment beyond the adjective already discounted above. The gap is sharper than usual given that the material flowing through the product includes confidential deal documents and a named external model provider sits in the processing path.

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

The vendor names no certification, audit type, report or trust portal. What stands in their place is a run of adjectives: the product is described as institutional grade and privacy centric, and as maintaining the highest standards of data security and compliance. This index already catalogues institutional grade as an unverifiable quality claim, and privacy centric is the same construction. Third instance in this session of a young vendor substituting a grade adjective for a credential, and it earns nothing.

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 licence.
Vendor Published

The vendor holds no licence, registration or supervised status, and none would be expected: it sells a modelling tool to regulated firms rather than performing a licensed activity itself. Worth noting for a buyer that models built with agent assistance may feed valuations and materials that sit inside the customer's own regulatory obligations, and the vendor publishes nothing addressing that boundary.

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 vendor publishes no evaluation methodology, testing regime or governance position for the agent's behaviour. The live question in this setting is not protected class fairness but selection and reconciliation: when two sources disagree on a figure, the system decides which to prefer, and nothing published describes how that judgement is made or evaluated even though the reconciliation capability is marketed as a headline feature.

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 vendor publishes no liability position, indemnity, accuracy warranty or remediation route. The exposure is unusually direct compared with the research assistants elsewhere in this pocket: this agent writes into a live valuation model rather than producing a document a person reads and judges, so an error enters the arithmetic of a transaction rather than a summary of it.

Integration and Deployment
Model Supply Chain Disclosure
AA on Model Supply Chain DisclosureEvery party between the customer’s data and the output is enumerated by name, canonically through a public subprocessor list naming the model providers.
Vendor Published

The most granular supply chain disclosure in this index. The provider is named on the vendor's own site, and a jointly published technical account names specific model versions and maps each to the workflow it serves with a stated reason: one reasoning model replaced a chain of prompts and verification steps for multistep financial reasoning, a smaller model cut latency to roughly a third per turn for long multi step work such as analysing confidential information packages and reconciling models, and several others were evaluated in the process.

A buyer can therefore tell not only whose models are involved but which one answers which kind of question, which is more than any other vendor here discloses. Graded on disclosure rather than architecture: the same transparency reveals a single provider dependency with no alternative or failover described, but that is a concentration the disclosure exposes rather than a gap in the disclosure itself.

Core Systems and Integration Depth
BB on Core Systems and Integration DepthNamed systems or a documented public API, with the depth or the production evidence left open.
Vendor Published

Integration depth is the product's central design choice rather than a feature list. The agent operates inside the spreadsheet where the modelling actually happens, unifies a firm's internal files with public disclosures and a named licensed data source into one searchable plane, and delivers into the document and presentation formats the same teams already use. Held at B because the environment it inhabits is another company's, and this vendor is not itself the system of record for any function.

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

The vendor publishes no hosting model, region, residency commitment or tenancy position. Material here because the product ingests confidential information packages, internal investment files and live models from banks and private equity managers, and a buyer in that position needs to know where that content travels and comes to rest.

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

The vendor publishes no price on its own site. Flagged as incomplete rather than settled: the product carries a listing on a major software marketplace, and the standing rule here is to check a marketplace listing before grading commercial at C. A first year discount code circulating through a training partner also implies a published list price exists somewhere. Both checks are queued and either could move this grade.

Institution and Segment Coverage
BB on Institution and Segment CoverageNamed segments with dedicated material behind part of the coverage.
Vendor Published

Genuine breadth by institution type across the sell side and buy side: investment banks, private equity managers above 100 billion dollars in assets, global multi strategy hedge funds, corporate finance teams at large listed companies, and listed real estate developers.

Held at B rather than A because every segment is described as a category rather than counted or named, no client number is published, and no geographic coverage is stated, so a reader learns the shape of the customer base and not its size.

Head to Head

Compared With

Most editorial comparisons pair two vendors the index assesses as direct competitors for the same buyer. Some pair vendors that are adjacent rather than rival, where the useful question is where one ends and the other begins. Each carries a verdict, the buyer conditions that favor each vendor, and a graded side by side.

Alternatives to Endex

The closest documented capability profiles to Endex in the same categories, ordered by similarity across the same fifteen axes the index grades every vendor on. Closest documented profile, not a claim that either product does the same job. No vendor pays for placement.

A lighter documented profile than Endex

Documents Operational and Outcome Evidence and GLBA and Data Privacy Posture where Endex does not

A lighter documented profile than Endex

Documents Operational and Outcome Evidence where Endex does not

Documents Operational and Outcome Evidence and AI Safety and Data Stewardship where Endex does not

Documents Operational and Outcome Evidence where Endex does not

Similarity is computed axis by axis from published grades, not from a composite score. The index does not aggregate grades into a total. See the fifteen axes 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.

Contact us

Found a vendor we missed? Have feedback on the index? We’d love to hear from you.

AI FinTech Index

The AI FinTech Index is an independent index that tracks changes to AI vendors in financial services. It holds 489 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
September 5, 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.
© 2026 AI FinTech Index
3801 N Capital of Texas Hwy, Ste E240 · Austin, TX 78746