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Services

AI architecture, data, automation & modeling.

Four capabilities, at whatever depth you need: a few days of review, a working pilot, or a production build from start to finish.

01

AI Architecture

How the pieces fit together: where retrieval ends and the model begins, what each call costs, how it fails, and how a person checks its work. Designed around the constraints finance imposes, not a generic chatbot template.

  • Retrieval, agents and tool use, scoped to the job
  • Model choice backed by an eval set, not a vendor demo
  • Cost, latency and failure-mode analysis per call
02

Data Layer

Where most finance-AI projects quietly stall. We get your data point-in-time correct, reconciled and queryable, so retrieval returns the right figure and a backtest is not leaking next week into last month.

  • Pipelines for market, transactional, filing and alt-data feeds
  • Lineage, validation and entity resolution (the same issuer every time)
  • Vector and warehouse stores wired for retrieval
03

Workflows & Automation

A model behind an API is not a workflow. We connect the output into the tools your team already works in, with a person in the loop where a wrong answer is costly and hands-off automation where it is not.

  • Review and sign-off steps where the stakes are high
  • Integration with your existing systems and APIs
  • Monitoring for drift, cost and silent failure
04

Financial Modeling

Models for forecasting, valuation, risk and reporting, plus the AI that reads the filings and contracts behind them. Outputs show their working: the source line, the assumption, the date it was true.

  • Forecasting, scenario and risk models
  • Extraction from filings, contracts and statements
  • Analyst copilots and reporting automation

Engagement models

Pick the depth that fits.

Each one is scoped to a clear outcome and set up to roll into the next stage when it makes sense, not before.

Advisory

Consulting & Strategy

A few days

A focused look at what you already have, ending in a straight answer: is this worth building, what will it really take, and where will the data hurt you. Worth doing before you commit a quarter to it.

  • Architecture and data review
  • Feasibility and opportunity read
  • Build-vs-buy and a roadmap
Build popular

Prototype & Pilot

2–6 weeks

A working version on your own data, with an eval set that says how good it actually is. You get something real to judge against your current process, not a scripted demo that breaks on the second question.

  • Working prototype on your data
  • Eval set and baseline metrics
  • A concrete plan to reach production
Deliver

Full Project Delivery

Project-based

Design through to running in production: the data layer, the models, the workflow integration and the unglamorous wiring that usually gets cut first and then sinks the project.

  • Production design and build
  • Integration and deployment
  • Handover, docs and team enablement