07.27.2026

BMLL, SIGMA AI Benchmark Real-Time Execution Intelligence

07.27.2026
OPINION: Artificial, Yes. Intelligent? Maybe.

BMLL’s high-fidelity historical order book data will act as the analytical foundation for SIGMA’s AI-driven, real-time alerting, anomaly detection and decision support

BMLL, the independent provider of harmonised, continually engineered historical Level 3, 2 and 1 data and analytics for Capital Markets, announced a partnership with SIGMA AI, a provider of real-time actionable intelligence for financial markets. The partnership will combine BMLL’s high-fidelity historical order book data with SIGMA’s real-time engine to deliver a new intelligence layer that will allow market participants to instantly contextualise live market flow against deep historical benchmarks.

Actionable Insights through Combined Historical and Real-Time Analytics

The collaboration will create a unique product category by pairing the “normal” with the “now”. BMLL will bring its definitive historical Level 3, 2 and 1 order book data to establish baseline metrics around volatility, liquidity, spread behaviour, and auction dynamics. SIGMA AI will add its “Quant in the Cloud” streaming platform, applying continuous real-time computation, machine learning inference, and natural language delivery to live market data.

This combined approach will enable SIGMA’s platform users to detect anomalies, classify market regimes, and generate actionable alerts by continuously comparing live market conditions to the historical context provided by BMLL.

Anticipated users include exchanges and market data providers, low-touch and high-touch buy-side institutions, sell-side brokers and platform vendors, as well as market makers and quantitative firms. Use cases will include execution intelligence and benchmarking, market impact scoring and regime classification.

Paul Humphrey, Chief Executive Officer of BMLL, said: “We are delighted to welcome SIGMA AI to our BMLL Activate Data Credits Programme. Real-time analytics and decision support are a natural application layer on top of high-quality historical order book data; this partnership reflects our focus on enabling sophisticated, AI-driven workflows on top of BMLL data. Jointly, we will empower market participants with a new level of execution intelligence”.

Andy Simpson, Founder & CEO at SIGMA AI, said:  “We are very excited about our collaboration with BMLL. Together, we are building a production-ready analytics layer that generates actionable intelligence by comparing live conditions to a BMLL-derived historical context. BMLL’s strength is the definitive historical record, while SIGMA AI’s strength is continuous real-time computation, ML inference, and natural language delivery on live market data.

The combination will create a product category that doesn’t exist today and will help market participants measure execution quality against historical baselines.  The solution is intended for global trading. It will initially focus on Saudi Arabia, the UK and European instruments before expanding to the US, bridging the gap between historical reporting and real-time actionable insights.”

Partnership anchored in SIGMA’s participation in the ‘BMLL Activate’ Data Credits Programme

SIGMA AI is a participant in the ‘BMLL Activate – Data Credits Programme’, which is designed to help high-potential partners build, test, and launch new analytics or data-driven solutions on top of BMLL’s historical Level 3, 2 and 1 market data. The program helps firms move from idea to market validation more quickly by offering lower to no upfront data licence costs during the build phase. Under this programme, selected partners receive a defined allowance of BMLL data credits that can be redeemed for agreed, structured access to the BMLL Data Lab and/or BMLL Data Feed. This covers a defined scope of selected datasets, instruments, venues, and historical time windows, supporting rapid product development in a controlled way while providing a clear path to commercial rollout if the use case is successful.

Source: BMLL

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