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Banks, lenders, insurers, and fintechs.

Custom LLMs for Financial Services

Financial data is sensitive, heavily regulated, and full of jargon that general models misread. We train models that stay inside your perimeter and can explain their outputs.

Use cases

Where a custom model earns its keep

  • 01

    Ticket and email triage

    Route customer requests to the right queue with the reason codes your ops team already uses.

  • 02

    Credit memo drafting

    First drafts of underwriting notes in house format, grounded in the applicant file.

  • 03

    KYC document extraction

    Structured fields from IDs, statements, and filings with confidence scores for review.

  • 04

    Claims summarisation

    Condense adjuster notes and correspondence into decision-ready summaries.

Compliance

Designed around the rules you work under

Our security practices
  • Training and inference can run entirely inside your cloud account or data centre.
  • Model decisions come with traceable inputs to support model-risk-management reviews.
  • Data residency options for local storage requirements.

Case study

From the field

Financial ServicesIllustrative

Routing 40k support tickets a month with an 8B model

A frontier-API prompt pipeline was accurate enough to demo but too slow and too expensive at production volume.

Routing accuracy

Before: 71%After: 93%

Cost per 1K tickets

Before: $4.80After: $0.60

Where to start

Recommended services

Talk to someone who knows the rules

We'll walk through the compliance constraints before we suggest any model.

We reply within one business day (IST).

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