Directory of AI investment research platforms for asset managers

Aiera sells event intelligence and research infrastructure to asset managers, hedge funds, investment banks and brokerages, sourcing and capturing corporate and macroeconomic events and delivering them as live audio, sub second speech to text, human reviewed transcripts, generative summaries, sentiment scoring and search. It reports covering more than forty five thousand events a year across thirteen thousand companies and over a hundred macroeconomic entities, spanning earnings calls, investor days, shareholder and special situation meetings, conference presentations and regulatory briefings, and states that around a quarter of that content is available only through its platform. Delivery runs through a browser dashboard and mobile app, embeddable interface components, enterprise interfaces for downstream data providers and research platforms, and a model context protocol server for use inside customer artificial intelligence tools. The company frames its offering around governed access to licensed content, with entitlement management, source attribution and auditability presented as the conditions institutions need before putting language models near research material.

AlphaSense is a market intelligence and search platform for investment banks, hedge funds, private equity firms, asset managers, consultancies and corporate strategy teams, founded in 2011 by Jack Kokko after his time as a Morgan Stanley analyst. It combines natural language search and generative tools with a large licensed content estate spanning equity and broker research, company filings, event transcripts, expert call transcripts, news, trade journals and a client's own internal research. Generative features include summaries of every earnings call with sources cited, document level question answering, a grid product that runs the same question across many documents, financial data, and workflow agents. The company states it serves more than 6,500 organisations including 88 percent of the S&P 100, passed 500 million dollars of annual recurring revenue, and employs roughly 2,900 people. It reached a 4 billion dollar valuation alongside a 650 million dollar round co led by Viking Global Investors and BDT and MSD Partners with JP Morgan Growth Equity Partners, SoftBank Vision Fund 2, Blue Owl, Alkeon, Alphabet's CapitalG and Goldman Sachs Alternatives participating, and has bought three companies to widen the content and tooling: Sentieo in 2022, Tegus for 930 million dollars in 2024, and Carousel in 2025. Its disclosure practice is unusually complete for this index. It runs a trust centre carrying SOC 2 Type 2 attestation and ISO/IEC 27001:2022 certification with bridge letters and a published policy library, offers bring your own key and bring your own storage deployment alongside customer managed encryption keys, mirrors a customer's existing permissions so the assistant cannot surface content a user is not entitled to see, states that its AI is never trained on customer data and that it works only with model providers enforcing zero data retention, and states plainly that it is not currently certified to ISO/IEC 42001 while pursuing it and committing to publish progress.

Artian builds multi-agent systems for large financial institutions, letting them develop, customise and deploy agents that reason, adapt and collaborate across processes in capital markets sales and trading, wealth management and enterprise operations. Named use cases are operational rather than illustrative: pre-trade requests, break reconciliation and adviser relationship management. Its planner intercepts first and second line operations incidents and learns from an institution's own process context, including runbooks, standard operating procedures and business process graphs, then generates hundreds of interconnected agents that resolve recurring incidents. A natural language builder lets business technologists create agents alongside engineers, and an agent exchange is planned to allow collaboration across use cases and eventually across institutions. The platform is positioned around built-in model risk and data risk governance, human oversight and visible, explainable execution.

Auquan builds autonomous agents for the knowledge work that occupies analysts at asset managers, investment banks, private equity and private credit firms and insurers. Combining an agent architecture with retrieval augmented generation, it takes disorganised inputs spread across incompatible formats, document types and languages and produces finished outputs: investment memos, credit prescreens, responses to requests for proposal, business involvement and know your business screening, sustainability performance reporting and limited partner reporting. Its credit agent is presented as executing private credit workflows end to end. The company positions itself against horizontal generative tools aimed at shallow search and support tasks, targeting instead the multistep work that takes an analyst days.

Binocs runs a system of specialised agents built to mirror the structure of a real investment team, producing the analytical output a deal process consumes: commercial due diligence reports, investment memos, industry primers, screening summaries, market sizing and competitive benchmarking, growth strategy frameworks, sell side offering memoranda and credit assessment memos. It ingests offering documents, financials, industry research, earnings calls and curated third party data, and returns citation backed results. A private credit line adds automated covenant calculation that tracks and forecasts loan compliance across a portfolio alongside early warning dashboards. Buyers span private equity, private credit and venture debt funds, venture capital, investment banks, banks and non bank lenders, corporate development teams and strategy consultancies, and the product is offered either fully self serve or with an optional expert human layer.

Bipsync sells a research management system to institutional investment teams, positioned as the place where an investment firm's accumulated judgement lives rather than as an analytics engine. The platform ingests research automatically from email, documents and third party research providers, organises it across teams with optional model assisted tagging, and holds notes, memos, meeting records, diligence material and decisions in one searchable system of record with configurable workflows, permissions and compliance controls. In April 2025 the company launched a named suite of artificial intelligence features aimed at extracting usable findings from a firm's own proprietary research rather than from public market data, which is an unusual orientation in this market. A February 2026 integration with Arch, itself indexed here, pulls private markets documents including quarterly reports, financial statements, capital calls and distributions directly into the workspace, classified by fund, manager, asset class and effective date. Founded in 2012 by a former hedge fund analyst, headquartered in New York with engineering in Cardiff, the company states that clients represent over four trillion dollars in combined assets and include fifteen of the twenty largest United States university endowments and six of the eight Ivy League endowments.

BlueFlame AI is a generative AI platform for alternative investment managers, covering private equity, private credit, hedge funds, venture capital, wealth managers and funds of funds. It summarises confidential information memoranda, analyses board decks, extracts provisions from limited partnership agreements and non-disclosure agreements, manages due diligence questionnaires, drafts investment committee memos and generates investor updates, with an add-on organising unstructured deal documents into a searchable knowledge base. Clients connect to more than twenty system providers and draw on over fifty pre-built workflows, with native integration to the dominant private markets CRM and to market data platforms. Its automations are deliberately model-agnostic, drawing on several named language model providers, and it publishes a complete security position including an independent audit attestation, named hosting, single sign-on, role-based access and data residency controls. It was acquired by a major deal intelligence company in 2025.

Boosted.ai builds Alfa, an agentic research platform for asset managers, wealth managers and hedge funds that monitors what a firm cares about proactively rather than answering questions on request, learning a user's preferences and narrowing from general recommendations into specific agents that act on their goals. It began in 2017 bringing quantitative techniques to portfolio managers without requiring code or data science, and now spans idea generation, stock and portfolio analysis, risk monitoring, commentary creation and data extraction, with in line citations and voice powered research agents.

Brightwave is a New York AI research platform for investment professionals, founded by engineers from artificial intelligence and financial data infrastructure backgrounds. Its systems synthesise analysis across a corpus of hundreds of millions of documents including securities filings, earnings call transcripts, sell side research, breaking news, market data, expert network calls, investment memos and a customer's own internal knowledge base content, then distil the findings into written narratives structured the way an analyst would write them rather than returning a ranked list of passages. Users can also question primary sources directly. Buyers span the buy side, from owner operated registered investment advisers to crossover hedge funds, with a customer base reported at over 120 billion dollars of assets under management, and wealth management firms use it to prepare client facing market commentary. Funding totals 21 million dollars across a seed round in June 2024 led by Decibel Partners with Point72 Ventures, and a 15 million dollar Series A in October 2024 led by Decibel with OMERS Ventures.

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 organisation, 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 ten billion dollars or more, and offers a free trial in which a prospective fund submits a list of tickers ahead of earnings season.

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.

Evalueserve is a global research, analytics and operations firm founded in 2000 and headquartered in Zurich, delivering knowledge work to clients across several industries from delivery centres in India and elsewhere. Financial services is a separately addressed vertical with its own lines covering corporate and commercial banking, investment banking advisory, investment management and research, lending services, and risk and quantitative work. It qualifies for this index on the services hybrid rule because it also ships named, subscribable products rather than selling analyst time alone. Spreadsmart automates financial spreading for commercial lenders, converting borrower disclosures into structured credit inputs, and was highly commended as a lending technology provider at the 2024 Banking Tech Awards while the firm won best technology provider at Credit Strategy's 2024 Lending Awards. Insightsfirst is a market and competitive intelligence platform combining generative models, machine learning and configurable dashboards with subscription based personalisation and user level access control, and it also underpins early warning work that collects and vets large volumes of data to identify borrowers exposed to emerging financial or external risk. A distinguishing feature is Ask an Analyst, which routes a user query from the platform to the firm's own analysts for additional insight or a new study, making the human layer an explicit product component rather than a delivery detail. Peel Hunt is a named client, with its head of research publications on the record describing an equity research distribution deployment. Independent recognition includes leader placement in Forrester's 2024 wave for market and competitive intelligence platforms, category leadership in Chartis Research's 2024 credit lending operations report, inclusion in the Chartis QuantTech50, and a leader position in an analyst quadrant for generative AI service providers.

Finster AI is an agent orchestration and research platform for investment banks, asset managers, institutional investors and private credit firms, drafting investment memos, building client-ready briefing decks, modelling companies and markets ahead of transactions, and continuously monitoring sectors for competitive activity and market-moving events. Its answer to hallucination is architectural: a proprietary data pipeline grounded in verified corporate data rather than relying solely on general language models, ingesting regulatory filings, earnings transcripts and four named premium data feeds to produce cited, traceable outputs. Handling of material nonpublic information sits at the centre of the design, since front-office users require strict information controls and no tolerance for fabricated content in client communication or investment documents. Customers are tier-one banks and buy-side firms collectively managing over 800 billion dollars and employing more than a thousand analysts, and a major Swiss bank has invested.

FinTech Studios runs a generative AI intelligence engine for financial institutions and corporations, ingesting billions of open source signals across news, social media, regulatory filings and market data in more than 100 languages, augmented with premium and private sources, and turning them into attributable, source grounded insight. Products cover regulatory intelligence, market and macroeconomic research, conversational enterprise search and chart explanation, with generation running on named third party language models. The company describes the result as a continuously running intelligence substrate built for knowledge workers, developers and AI agents alike, and in 2026 opened it through a self serve platform with a free tier, arguing that continuous intelligence had previously been locked behind six figure enterprise contracts.

Hebbia analyses large private document sets for asset managers, private equity firms, investment banks and hedge funds through Matrix, a grid where each row is a document and each column is an analytical question, filled in by agents reading every page in parallel. Its architecture breaks a complex query into structured steps and routes each to a suitable model rather than relying on one, and every answer cell carries a citation resolving to the exact page, paragraph and sentence it came from, with analysts able to annotate, flag or overwrite any cell directly.

Hudson Labs, founded in 2019 in Toronto and formerly called Bedrock AI, builds finance specific language models for institutional equity research. Its founders are Kris Bennatti, a chartered accountant and financial data scientist published by the Harvard Law School Forum on Corporate Governance, and Suhas Pai, who wrote a book on designing large language model applications. The original product was systematic forensic risk analysis, reading the unstructured text of regulatory filings to surface accounting and governance concerns that standard screens miss, and in September 2025 the company launched the Co-Analyst, a research platform producing source verified summaries, guidance identification, multi document comparison and auto generated investment memos. The company frames its pitch against general purpose assistants, arguing they fail precisely where institutional investors need reliability most, on multi document analysis, guidance identification and numeric precision, and describes its own approach as proprietary retrieval, custom models, source selection, noise suppression and in house pipelines. It states the launch followed beta testing with hedge funds, asset managers and family offices representing over one trillion dollars of assets under management, with early results showing research time cut by more than half, and it serves asset managers, insurers and securities law firms. A high yield bond analyser is in development. Investors include Y Combinator, FoundersX Ventures, Born Capital, Zillionize, Brighter Capital and Immad Akhund, and named partners include Wolfpack Research and Enhancing Capital.

Linvest21 builds AlphaCopilot, an investment platform run by specialised agents including equity analysts, portfolio managers and virtual chief investment officers, sold to investment institutions and aimed at giving medium and smaller asset managers capability previously affordable only to the largest firms. It covers the chain end to end, from idea generation and research through portfolio construction, risk management and performance analysis to customised client communications, and a 2025 addition delivers real-time global macroeconomic analysis in fifteen structured sections for chief investment officers and research leads. The company describes a human in the loop architecture in which the models recommend and people decide, and reports hundreds of billions of dollars in assets under its platform's supervision. Its founder spent 22 years at a major asset manager, latterly as chief technology officer of its global investment platform, and holds six financial technology and applied AI patents.

Model ML builds an AI workspace for investment banks, private equity firms, venture funds, asset managers and consultancies, where teams assemble AI Modules that run autonomously on a schedule or an event and produce client ready documents, spreadsheets and presentations in the firm's existing house formats. Its agents read across emails, filings, customer relationship records, presentations and third party datasets to draft pitch materials, investment committee memos, diligence deliverables and portfolio monitoring output, and it can be deployed single tenant inside a client's own cloud environment.

Needl.ai is a private enterprise AI platform for financial markets, founded in 2019 by Vikram Srinivasan and Kuntal Shah, with engineering in Bengaluru, India and a US entity, Needl Inc., registered in San Francisco. It positions itself as a context layer rather than a model builder, running inside a customer's own environment and answering questions from that firm's own material: email, drives, wikis, virtual data rooms, CRM records, subscribed research and internal notes, alongside filings, news and roughly 20,000 monitored external sources. Four product capabilities are sold: knowledge management with cited answers, report automation covering filing summaries and credit memos, market intelligence with ranked and routed alerts, and a causal intelligence layer that models the drivers behind market moves rather than scoring them. Eight named workflows sit on top, among them automated due diligence with a cited investment committee memo, credit rating report generation, compliance event monitoring across regulators, a relationship manager copilot checked against mandate and suitability, financial modelling populated from filings, analyst note generation, real time trading intelligence and portfolio monitoring. Buyers span private equity and private credit, asset management, banking and capital markets, wealth management and private banking, and credit rating agencies. Named customers include GrayArch Partners, Scotia Wealth Management, Oaklane Capital Management and MSquared, with unnamed deployments described at a large consultancy, a major ratings agency, a credit agency running 750 million dollars of assets and a trading desk running 10 billion dollars. The company reports roughly 45 staff and holds seven patents on its retrieval and reasoning engine. Its disclosure is unusually complete for a firm of its size: it names five foundation model families as interchangeable commodity infrastructure and supports customers bringing their own model, names eleven source systems it connects to, enumerates ISO 27001, SOC 2 Type II and CASA with a Google CASA assessment, states that it never trains shared models on customer data, and cites a placement on the S and P AI Benchmarks Long-document QA leaderboard run by Kensho. Set against that, its marketing carries a headline claim of no hallucination and accuracy figures quoted as high as 100 percent and above, which is not a figure that can exist.

Obin AI builds what it calls an agentic workforce for financial institutions, deploying agents that run defined workflows end to end rather than producing drafts for a person to finish. The platform targets continuous monitoring, underwriting at scale and earlier risk detection across private credit, equity, lending and insurance, and its central design claim is that agents operate inside a firm's own controls and audit boundaries, encode that institution's specific logic and decades of accumulated context, and produce traceable and inspectable outputs. The architecture is described as open and free of lock in, with the enterprise retaining full ownership of the intellectual property. Founded by a former head of artificial intelligence at a major global bank and a former Google executive, it emerged from stealth in March 2026.

Quartr structures the first party material public companies publish about themselves, live earnings calls, real time transcripts, conference and capital markets day audio, filings and slide presentations, and sells it in two forms: Quartr Pro, a research platform where investment professionals query across company materials with every answer linked back to the original source, and Quartr API, a data feed that other research platforms and artificial intelligence systems build on. Coverage runs to more than 13,000 public companies across over 65 markets, with a single interface carrying consistent identifiers across audio, transcripts, filings and slides, and entity structuring across companies, events, people, products, topics and reported metrics linked over time. The company describes itself as infrastructure for company research rather than as an analysis product, and its stated argument is that investor relations material was the primary input to qualitative research and had never been made queryable at scale. Headquartered in Stockholm with offices in New York and Dublin and led by co founder and chief executive Oscar Kuntzel, it states that more than 700 financial institutions and technology companies use its products, including hedge funds, asset managers, equity researchers and investor relations teams, and it also runs a free consumer mobile app carrying the same event material. It reports triple digit growth and net revenue retention of roughly 120 percent. Funding has come in successive rounds from Altos Ventures, which led an 18 million dollar round in 2026 and is now the largest shareholder, alongside the Nordic bank SEB, Ohman and Yanno Capital.

Rogo is a generative AI platform built for investment banks, private equity firms and asset managers, pulling filings, transcripts, deal databases, market data and a firm's own data rooms into one place so an analyst can ask questions in plain language and get answers with citations. Its agent, Felix, carries out the long running work that has traditionally filled the analyst and associate tiers, including deal screening, information memorandum drafting, data room diligence, model construction, pitch material assembly and buyer outreach, and commits the output back into the firm's own tools.

Rowspace turns a financial firm's own history into working intelligence, connecting structured and unstructured data across document repositories, investment and accounting systems and legacy infrastructure, then applying a finance native lens that reflects how that particular firm reconciles information, interprets discrepancies and reaches decisions. Institutional investors, private equity firms and credit desks use it for portfolio monitoring, cross decade analysis and credit portfolio optimisation, and it deploys directly into customer environments so data never leaves their control, delivering output through its own interface, inside spreadsheet and collaboration tools, or into existing data infrastructure.

Samaya AI builds expert knowledge agents for financial institutions on its own custom trained financial language models rather than general purpose ones, arguing that factuality matters more than fluency in this work. Its agents synthesise sector wide investment reports, assemble investment presentations by reasoning over a firm's proprietary documents, and answer complex questions across millions of real time sources with cited evidence attached, and a newer agent models the economy to produce quantitative predictions on questions such as the effect of tariffs on output. It serves sell side research, sales and trading, investment banking, hedge funds and asset managers.

Terminal X, built by Project Pluto Inc, is an agentic research platform for institutional investors, founded in New York in August 2022 by chief executive Hyun Hong, who spent a decade in mergers and acquisitions, private equity and portfolio management, and chief technology officer Kibum Kim, previously more than ten years at Google as a tech lead across Chrome, Search and the TensorFlow team. Its argument is that general purpose assistants fail investment work because they know nothing about a firm's own thesis, risk limits, investment committee preferences, trusted data vendors or memo conventions. The platform therefore indexes a firm's proprietary material alongside public sources, parsing Excel models at cell level, emails, past deal memos and subscribed research into sentence level retrieval, and combining that with more than a hundred million external sources including filings, earnings transcripts, investor presentations, financial supplements, broker research and news. It supports memo writing, due diligence, thesis validation and portfolio monitoring, and separately publishes data interfaces for market intelligence and event narratives. Its architecture is deliberately model agnostic: a query is decomposed into hundreds of discrete micro steps, each evaluated in milliseconds for the nature of the task, the reasoning required and the quality against latency tradeoff, then routed to whichever frontier model is performing best for that input across the GPT, Claude and Gemini families, with new models added as they launch and prompts hand tuned by former bankers and hedge fund managers. Buyers span hedge funds, private equity and buyout funds, asset managers, family offices, venture firms, sovereign wealth funds, pension funds, securities firms and corporate finance teams across the United States, Japan and Korea. It raised a Series A including DG Daiwa Ventures, the joint venture between Digital Garage and Daiwa Securities Group.