Reflexivity: Initiation of Coverage

GAII Intelligence defines the AI Research & Intelligence market as software that applies generative and agentic AI to the research process of professional investors: locating candidate securities, assembling and interrogating evidence, producing written analysis with traceable sources, and monitoring positions once held. Buyers are hedge funds, long-only managers, multi-manager platforms, family offices and allocators; the economic buyer is typically the chief technology officer, the head of research, or a portfolio manager with a technology budget.

Capabilities we treat as mandatory

• Evidence retrieval at scale: the ability to search and reason across regulatory filings, transcripts and news, and across documents the client supplies.
• Source traceability: every material claim in an output must be reachable back to the passage that supports it.
• Institutional data handling: a stated position on where client data goes, how long it is held, and whether it is used for model training.

Capabilities we treat as differentiating

• Persistent state: the system remembers a thesis, a coverage list or a position between sessions and acts on it without being re-prompted.
• Workflow surfaces: delivery inside the applications analysts already use — the spreadsheet, the research management system, email and messaging.
• Owned or exclusive content: material that a competitor cannot obtain by signing the same third-party contract.
• Published evaluation: a measured, disclosed accuracy methodology rather than an assertion of quality.

Reflexivity competes with AlphaSense and Bigdata.com for market intelligence, but on quantitative and thematic questions rather than document search. Boosted.ai is the closest comparison in our coverage for buy-side agents; Bloomberg and Kensho are the incumbent reference points.

The following are the capabilities and characteristics that, in our assessment, most distinguish Reflexivity within the AI Research & Intelligence market. Each is drawn from publicly documented product capability, published interviews with management, or independent hands-on review.

• Practitioner founders and backers: Founders from Duquesne, Lombard Odier and Fortress, and backers including Stanley Druckenmiller, Greg Coffey and Thomas Peterffy.
• Strategic distribution: Interactive Brokers is a minority owner and runs Investment Themes on Reflexivity across its platforms; Akbank uses it for AI stock insights.
• Bundled licensed data: LSEG Datastream with I/B/E/S, S&P Global, Cboe, Dow Jones and Reuters with no separate data contracts.
• Differentiated architecture: Code-executing agents over a knowledge graph of 40,000+ securities, 900+ themes and 10m+ relationships.
• Open engineering writing: Public posts on evaluation, model-migration cost and explicit failure handling.
• Microsoft 365 Copilot presence: A Copilot plugin launched in June 2026.

The following are factors that prospective clients should weigh, and areas where our public review did not find sufficient evidence to reach a settled view. Several are common across vendors at this stage of the market and are not specific to Reflexivity. We encourage prospective clients to raise each of them directly with the company; we have done the same, and will update this note as answers arrive.

• Security evidence: SOC 2 Type 2 is claimed without a report date or trust centre; ISO 27001, SSO/SAML/SCIM and admin audit logs were not located.
• Model providers: AI subprocessors are not disclosed, and marketing describes infrastructure "air-gapped from public AI models" while company posts discuss frontier-model deprecations. Buyers should obtain written terms.
• Privacy terms: The published privacy policy dates from January 2022 and cites the defunct Privacy Shield; data terms need to be negotiated.
• Traction evidence: Institutional client names come from one secondary source, ARR is not disclosed, and no case studies were located.
• Evaluation: The evaluation method is described but no results are published; buyers should test on their own questions.
• Scale: About 28 people on the roster and no go-to-market roles posted; buyers should assess support capacity.
• Funding: No round located since the $30m Series B in October 2024.
• Content scope: Broker research, expert transcripts and client document corpora were not located.

Knabble, Inc., trading as Reflexivity and formerly Toggle AI, was founded in New York in 2019 by Jan Szilagyi, formerly co-CIO of global macro at Lombard Odier after Duquesne Capital, Giuseppe Sette and Armenak Mayalian. It has offices in New York, London and Tokyo, acquired Atom Finance in May 2024 and rebranded as Reflexivity later that year.

Reflexivity raised a $10.5m Series A in 2021 and a $30m Series B in October 2024 led by Greycroft and Interactive Brokers, with Stanley Druckenmiller, Greg Coffey, General Catalyst and SoftBank; $40.5m is disclosed. Interactive Brokers is a minority owner. The company reports institutional clients with more than $325bn in combined assets.

Company-reported figures are shown as such and are not independently verified. Verification is carried into the vendor questionnaire.

Reflexivity presents a market-intelligence platform built on a knowledge graph and code-running agents. Figure 2 sets out our assessment of how it maps onto the investment workflow.

Deep Research

Agents that write and run Python over licensed data and the knowledge graph.

Portfolio Insights

Daily insights, alerts and attribution on uploaded holdings.

Scenario Analysis and Screening

Hypothesis tests, backtests and thematic screening.

Copilot and API

A Microsoft 365 Copilot plugin and a RESTful API with white-label options.

Scope of the product today

We did not locate an Excel, Teams or Office add-in, a public MCP server, broker research or expert transcripts.

Reflexivity combines an analytical code library, a proprietary knowledge graph and language models as the reasoning layer; agents debug their own code and are designed to fail explicitly when data is missing.

The company describes a "strike score" evaluation across five dimensions but publishes no results, and does not name its model providers.

Reflexivity bundles LSEG Datastream with I/B/E/S estimates, Cboe prices, Nasdaq, S&P Global financials and transcripts, Dow Jones, Reuters, MT Newswires and Benzinga news, Quartr presentations, EDGAR filings and macro data, across 40,000+ securities.

Broker research, expert transcripts and client document corpora were not located; clients can upload portfolios.

Reflexivity fits idea generation and monitoring for macro, thematic and quantitative investors: themes, screens, scenario tests and portfolio alerts.

Delivery into the desktop is limited to a Copilot plugin and data export.

Reflexivity claims SOC 2 Type 2 with annual third-party audits, dedicated compute, end-to-end encryption and no persistent storage of client data. Figure 3 sets out what our public review located.

We would encourage buyers to request the SOC 2 report, a current privacy policy and DPA, model-provider and retention terms, SSO and admin audit logs.

The offsetting factor is distribution: Interactive Brokers and Akbank run Reflexivity for their own clients, implying diligence by regulated firms.

Institutional pricing is not published. IBKR clients receive a two-week trial and then Basic or Full tiers, and IBKR describes its AI tools as included at no extra cost.

Bundled data removes separate licence costs — an advantage few peers offer. Buyers should confirm data redistribution terms.

Reflexivity sits in the Emerging quadrant of the GAII Intelligence Matrix, held back by data scope and enterprise evidence.

GAII initiation universe, 20 October 2026. Scores as currently published on the GAII Intelligence page; preliminary and based on public information.

11.1 Where Reflexivity is strongest relative to peers

• Against document platforms, on quantitative and thematic analysis with code execution.
• Against data vendors, on agents that reason over bundled data.
• Against peers requiring separate licences, on bundled market data.

11.2 Areas of narrower functional focus

Reflexivity has built depth in quantitative analysis rather than content breadth or enterprise documentation.

• Content: no broker or expert research.
• Enterprise: stale privacy policy; SSO not located.
• Delivery: no Office add-in or MCP server.
• Scale: small team; no recent funding.

Scores are on a 0–10 scale. Each dimension score is the mean of its sub-criteria, and the GAII Overall Score is the weighted mean of the six dimensions. The detailed sub-criteria scores that build each dimension are set out in Appendix A.

These are the areas where our public review did not find sufficient evidence to form a settled view. We have put them to the company and will update this note when they are answered. Prospective clients may find them a useful agenda for their own evaluation call.

• The SOC 2 Type 2 report period and auditor.
• A current privacy policy and DPA.
• Which model providers process client data, and on what terms.
• Availability of SSO/SAML, SCIM and audit logs.
• How "no persistent storage" fits portfolio uploads and alerts.
• Institutional pricing.
• Named institutional references.
• Revenue scale and split between retail and institutional.
• Runway and funding plans.
• Plans for an Office add-in or MCP server.
• Data redistribution terms for bundled sources.
• Current headcount.

This note is an assessment of a vendor against a defined framework, not a recommendation to buy or to decline. The following are the considerations we would put at the centre of an evaluation of Reflexivity specifically.

If you are a fundamental equity manager

• Test scenario analysis on a live thematic question.
• Compare portfolio alerts with your current monitoring.
• Check coverage of your markets.

If you are responsible for technology or vendor risk

• Open with Figure 3; request the SOC 2 report and current DPA.
• Confirm model-provider terms in writing.
• Assess support capacity for a firmwide rollout.

If you are assessing the category rather than the company

• Quantitative agents are a distinct category from document copilots.
• Bundled licensed data lowers adoption friction.
• Brokerage distribution is a route to scale for research AI.

Each dimension score in Section 12 is the mean of the sub-criteria below.