BestEx Research: Initiation of Coverage

GAII Intelligence defines the Quant, Portfolio & Analytics market as software and model services that apply machine learning to the quantitative core of investment management: generating return and risk forecasts, constructing and rebalancing portfolios, measuring and attributing performance, and estimating and minimising the cost of trading. Buyers are portfolio managers, quantitative researchers, heads of trading and the chief investment officers and technology teams who sign off on systematic processes.

Capabilities we treat as mandatory

• Point-in-time and backtest integrity: model inputs and simulations free of look-ahead and survivorship bias, with a documented method a quant team can reproduce.
• Out-of-sample and live evidence: performance or cost-reduction claims supported by live or held-out results, not only in-sample backtests.
• Institutional data handling: a stated position on where client holdings and order data go, how long they are held, and whether they are used for model training.

Capabilities we treat as differentiating

• Explainability of signals: forecasts, weights and cost estimates traceable to their drivers in a form a portfolio manager or risk committee can challenge.
• Independent, verifiable track record: live results published through regulated funds, third-party ratings or client-run A/B tests over several years.
• OMS/EMS and data-platform integration: native delivery into order and execution management systems, FIX, and the firm's data platform and Python stack.
• AI-assistant access: models and analytics reachable from the assistants portfolio managers and traders already use, through APIs or MCP, without loss of rigour.

BestEx competes with bank and broker algorithm suites, with independent execution and analytics providers such as Virtu Analytics, Abel Noser and Tradeweb, and, for its AMS One platform, with technology vendors that sell algorithm frameworks to the sell side.

The following are the capabilities and characteristics that, in our assessment, most distinguish BestEx Research within the Quant, Portfolio & Analytics market. Each is drawn from publicly documented product capability, regulatory filings, published interviews with management, or independent review.

• Research depth: Execution models designed and documented in white papers, with out-of-sample validation on a full year of executions.
• Live A/B evidence: IS Zero tested against VWAP across more than 140,000 parent orders (company).
• Configurability: Strategy Studio exposes 150+ parameters without code; banks can build branded algorithms on AMS One.
• Asset-class reach: Global equities and futures on 21 exchanges, with 24×5 futures trading since April 2025.
• Shipping velocity: Four launches in 2026, from dark execution to AI-assistant access.
• Profitability: First profitable year in 2024 and volume up 87% (company).

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 BestEx. 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.

• Assurance: SOC 2, ISO 27001 and SSO documentation not located.
• AI data handling: Pulse AI runs through third-party assistants such as Claude and ChatGPT; no data-handling or no-training terms published.
• Evidence: Cost-saving and A/B results are company-run; no independent evaluation located.
• Scope: Execution and cost analytics only; no optimiser, factor model or portfolio risk.
• Pricing: No prices or pricing model published.
• Capital: Funding last disclosed in 2023; $15m in total.
• Regulatory status: The firm's own registrations were not located.

BestEx Research Group LLC was founded in 2017 by Hitesh Mittal, formerly global head of trading at AQR Capital Management and, for more than a decade, head of algorithmic trading and POSIT at ITG. It is headquartered in Stamford, Connecticut, with offices in London and Bengaluru and development teams in India and Armenia. Its platform has been live since 2019.

BestEx raised a $5m Series A from QC Ventures, affiliated with the quantitative manager Quadrature, in December 2020 at a $50m valuation, and a $10m follow-on from existing investors in March 2023 at $110m. The company reported its first profitable year in 2024. Revenue is not disclosed.

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

BestEx offers execution algorithms, a platform for running them, and cost analytics. Figure 2 sets out our assessment of how it maps onto the quant and portfolio workflow.

Execution algorithms

IS Zero, implementation shortfall, liquidity-seeking, Curator dark and close algorithms across equities and futures.

AMS and AMS One

Cloud algorithm management with Strategy Studio, smart order routing, monitoring, A/B testing and integrated TCA; AMS One lets banks and brokers run it as their own business (June 2026).

Pulse Analytics

Pre-trade market impact models for futures (2025) and US equities (September 2026), by dashboard and REST API.

Pulse AI

Conversational access to Pulse through clients' own AI assistants (August 2026).

Scope of the product today

We did not locate portfolio optimisation, factor risk models or return forecasting for clients; BestEx sits at the execution end of the workflow.

The core models are quantitative rather than generative: the Pulse impact model combines more than one million institutional parent orders with cost sensitivities estimated from TAQ data, built on a "meta-order" view of daily supply and demand. The company states that the model is not built with AI; generative AI is the interface.

Validation is out of sample on a full year of executions, and execution algorithms are compared by live A/B tests. Both are company-run.

BestEx draws on tick and TAQ market data, minute bars, volume, volatility, spread and depth estimates, and its own institutional execution history across equities and futures.

It does not use or supply fundamental, alternative or factor data; broker-neutral post-trade TCA on clients' wider executions is scheduled for Q1 2027.

BestEx fits trading desks and quant teams that want measurable execution quality: configurable algorithms, A/B testing and pre-trade cost estimates that can feed position sizing.

Portfolio construction, risk and attribution sit with other vendors, and named OMS/EMS integrations were not located.

BestEx runs a cloud-hosted, globally co-located platform and white-label deployments for sell-side firms. Figure 3 sets out what our public review located.

We would encourage buyers to request a SOC 2 report or equivalent, SSO and access-control documentation, data-handling and no-training terms for Pulse AI, and the firm's regulatory registrations.

The offsetting factor is operating evidence: a live platform since 2019, a bank partner in Scotiabank and a reported first profitable year.

Pricing is not published, nor is the commercial model for algorithms, AMS One or Pulse.

Buyers should request pricing alongside a structured A/B test against current algorithms.

BestEx sits in the Emerging quadrant of the segment matrix, with the highest overall score of the three companies in the segment so far; as an execution specialist it is scored partly on portfolio-construction criteria it does not target.

GAII Quant, Portfolio & Analytics coverage, 21 October 2026, scored on the segment variant of Data & Content and Workflow Fit; not directly comparable with Research & Intelligence or Risk, Compliance & Surveillance scores.

11.1 Where BestEx is strongest relative to peers

• Against bank algorithm suites, on independence and measurable cost evidence.
• Against TCA vendors, on predictive pre-trade models rather than historical reports.
• Against algorithm-framework vendors, on research-tested algorithms delivered with the platform.

11.2 Areas of narrower functional focus

BestEx has built depth in execution rather than enterprise documentation or portfolio tools.

• Assurance: no certifications located.
• Pricing: not published.
• Scope: no portfolio construction.
• Capital: small disclosed 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.

• SOC 2 or ISO 27001 status.
• SSO, SAML and access controls.
• Data handling and no-training terms for Pulse AI.
• Which assistants and integration method Pulse AI uses (API, MCP).
• Regulatory registrations of the firm.
• Named OMS/EMS integrations.
• Pricing model for algorithms, AMS One and Pulse.
• Client count and named references.
• Independent evaluation of IS Zero and Pulse.
• Revenue and runway.
• Funding plans.
• Global equities cost model timing.

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 BestEx specifically.

If you run portfolios, quant research or trading

• Run an A/B test of IS Zero against your current VWAP algorithm.
• Use Pulse cost estimates in position sizing.
• Keep portfolio construction with existing tools.

If you are responsible for technology or vendor risk

• Open with Figure 3; request SOC 2 and SSO.
• Review Pulse AI data flows through your assistant.
• Map FIX and OMS/EMS connectivity.

If you are assessing the category rather than the company

• Execution analytics are becoming predictive.
• AI assistants are reaching trading analytics.
• Independent algorithm providers now sell platforms to banks.

Each dimension score in Section 12 is the mean of the sub-criteria below. Data & Content and Investment Workflow Fit use the Quant, Portfolio & Analytics segment variant.