AI IS A NEW KIND OF CHALLENGE ACCEPTED.
We know how to use AI to solve the reasoning and non-deterministic problems that traditional software cannot — and we have put those systems live for clients, not just built prototypes.
Two ways we bring AI.
Our whole consulting practice is AI-skilled, and many of our people are already embedding those skills directly into client work — data estates, market data platforms and front-office delivery.
We have built a team focused solely on AI engineering, for clients who want the AI problem owned end to end rather than added to an existing workstream.
Most of the difficulty in AI sits around the model, not in it.
Good data is a necessary starting point, then come the questions around design and engineering: where reasoning actually adds value, how you check output you cannot fully predict, and how the system behaves when the model gets it wrong.
We bring the same discipline to these problems that we bring to mission-critical data platforms, so a system that impresses in a demo still holds up when it is live and under load.
1. The data isn’t AI-ready : Twenty years of tick data, bespoke schemas and undocumented processes. A model can’t reason over what it can’t reliably reach.
2. Confident answers, no evidence : A plausible answer with no audit trail is worse than none at all when the regulator, the risk desk or the P&L is on the other end.
3. Proofs of concept don’t scale: standing something up in an isolated environment for a subset of users doesn’t always lead to production success. We take systems to production, and provide ongoing support in the same way we support your data estate.
Two ways in.
'Talk to your data' - we have example production agents allowing a new paradigm of data exploration and democratised access via natural language search and interogation.
Explore one of our accelerator projects. A multi-agent project to help you support complex data systems? A Trade Surveillance agent transforming alert investigation capabilities?
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Agentic AI for Supporting kdb+ Applications
Read MoreAn Agentic AI solution for supporting kdb+ applications
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We Built an AI Agent That Knows When It Doesn’t Know
Read MoreHow we built an AI agent that investigates telemetry issues, reasons through evidence, and clearly signals when confidence is low.
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From Alert Overload to Insight: Reimagining the Surveillance Analyst’s Day with AI Augmentation
Read MoreAI-augmented surveillance helps analysts cut through alert overload by surfacing insights, bridging data gaps, and accelerating investigations - without replacing human judgement.
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From Q-rious to Q-ompetent: Which LLM is Best At kdb?
Read MoreBenchmarking LLMs at creating kdb+/q code
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Using Databricks Genie to Analyse Capital Markets Data
Read MoreHow to make the most out of Databricks AI/BI Genie with Capital Markets datasets