AI Models
AI for Finance

Analysis and reporting with precision.

Accelerate the close, explain variances, draft board packs and stay on top of controls — with humans firmly in the approval loop.

Finance assistant
Explain the main drivers of the operating-expense variance versus budget.
Three drivers: higher contractor spend in engineering, an earlier-than-planned marketing campaign, and a one-off software renewal. Timing explains roughly half.
Ask anything…
The challenge

What holds finance teams back

  • Month-end crunch

    Reconciliations and commentary pile up at the worst time.

  • Spreadsheet sprawl

    Insight hides across dozens of files and versions.

  • Control pressure

    Documentation and evidence take longer than the work itself.

Use cases

Six ways to put AI to work, today

Analysis, reporting and controls with precision.

  • Variance commentary

    Plain-English explanations of what moved and why.

  • Board-pack drafting

    Narratives and summaries from your numbers.

  • Policy Q&A

    Instant answers on expense, procurement and finance policy.

  • Invoice extraction

    Pull structured data from documents reliably.

  • Control documentation

    Draft narratives and evidence summaries.

  • Forecast scenarios

    Explore what-ifs conversationally.

How it works

From first prompt to everyday workflow

  1. 01

    Upload data

    Exports, statements and policies.

  2. 02

    Analyse

    Ask questions and explore variances.

  3. 03

    Draft

    Generate commentary and reports.

  4. 04

    Approve

    Finance owners review and sign off.

Agents & skills

Agents built for finance

Give an agent a goal and it plans the steps, uses the skills you grant and reports back — with approvals wherever you want a human in the loop.

  • Variance commentary: Plain-English explanations of what moved and why.
  • Board-pack drafting: Narratives and summaries from your numbers.
  • Policy Q&A: Instant answers on expense, procurement and finance policy.
Explore agents
Agent run · live
  1. Understand

    Intent & context

    Done
  2. Plan

    Break into steps

    Done
  3. Act

    Run skills & tools

    Running
  4. Deliver

    Verified result

    Queued
Outcomes

What changes when you switch it on

  • Outcome 1

    A calmer close

    Commentary and reports drafted in hours, reviewed by experts.

  • Outcome 2

    Clearer insight

    Ask questions of your data in plain language.

  • Outcome 3

    Audit-ready

    Logs and documentation built in, not bolted on.

Under the hood

Foundational models, plus proprietary architecture

Every leading open model family, made sharper by the layer we built around them.

  • Routing

    The best model for each request, automatically.

  • Memory

    Your finance context, remembered securely.

  • Skills

    Search, read, write and call your own tools.

  • Agents

    Goal-driven workers with guardrails.

Security posture

All controls healthy

Continuously monitored

  • Encryption in transit & at rest
  • SSO & scoped API keys
  • Audit logs for every action
  • Your data never trains shared models
Security & control

Enterprise-grade from day one

  • Your data is never used to train shared models
  • Encryption in transit and at rest
  • Roles, scoped API keys and approval steps
  • Audit logs, SSO and private deployment options on higher plans
FAQ

Finance questions, answered

Does AI make financial decisions?

No. It drafts and analyses; your team reviews and approves.

Are calculations reliable?

Use structured data skills for calculations and always review outputs.

Is financial data secure?

Yes. Encrypted, access-controlled and never used to train shared models.

Are there audit logs?

Yes, on Scale and Enterprise plans.

Bring AI to finance — today

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