For financial teams & organizations

AI agents for better decisions & smarter workflows

We build custom AI workflows that turn complex information into clear, source-backed analysis for high-stakes decisions. Connected to your data and tools, with your team in control.

Research documents become an approved output with three thin ranked lines, each marked with a green check.

Built around the way your team works

01

Analysis & research

Analyze documents, financial and market data from internal systems, partners and external sources. Compare trends, assess risks and produce sourced briefs.

Evidence-backed insights
02

Decision automation

Use historical data, decisions and outcomes to train AI models for future decision support, automation and improvement, with human approval checks where required.

AI decisions, human control
03

Workflow automation

Connect databases, CRMs, messaging apps and business tools to process requests, update records and coordinate follow-ups.

Connected operations

Experience

15+ years of experience in ML and AI, combining predictive analytics, custom modeling and workflow automation for leading organizations across finance, government, defense, healthcare, brands and media.

Selected results across prior projects

95%

Time saved

Through automation of research and insight generation workflows.

+92%

Goal achieved

Improvement in the project's target metric through AI-informed optimization.

>90%

Accuracy

In selected behavior-prediction tasks.

Selected clients

Senseera
CyberWell
MAFAT / DDR&D
Ministry of
Diaspora Affairs
Sheba Medical Center

From one workflow to a working system

Estimated timing for a first workflow, followed by ongoing support.

  1. 01

    Discovery

    Map the workflow, data sources and review responsibilities. Establish the time and effort it takes today.

    1–3 days
  2. 02

    Scope & controls

    Agree success criteria, access boundaries and where human approval is required.

    3–5 days
  3. 03

    Build & validate

    Connect your tools and test against completed cases. Verify figures, citations and exception handling.

    2–6 weeks
  4. 04

    Monitor & support

    Roll out with your team. Track quality, time saved and cost, then improve from reviewer feedback.

    Reviews every 1–2 weeks

Model-agnostic and
kept up to date

We select LLMs and specialized models for accuracy, speed, cost and privacy. Deploy in your cloud or locally, with newer models introduced when testing shows a measurable improvement.

Tell us what your
team needs

Where does your team spend time gathering evidence, preparing analysis or checking outputs? Let’s identify a practical first workflow and agree the data, review process and measures of success.