Case Studies | SaaS B2B

AI claims intake and triage for litigation funding

AI Claims Intake and Triage

About

A SaaS B2B business working with Cloud Combinator on AWS. The client is anonymised at their request.

Challenge

The challenge had four focus areas.

The manual screening burden

Every inbound application had to be checked against the client's hard-no criteria, jurisdiction, claim type, funding ratio, claim value cap, and the presence of a counsel's opinion and ATE insurance, before any deeper work could begin. Doing this by hand across many bundles consumed underwriter time that was better spent on judgement.

Deep, cross-document analysis

Passing an initial screen is only the start. The real work is reading counsel's opinions, defence correspondence, pleadings and evidence together, reconciling conflicting signals, and forming a view on prospects, quantum and risk. This is demanding and time-consuming to do consistently at volume.

Consistency, auditability and control

An underwriting decision system has to be trustworthy. Outputs needed to be consistently structured, every step needed a full audit trail, and the design had to keep a human underwriter in control of the final decision rather than automating it away.

Secure handling of sensitive legal material

Claim bundles contain confidential legal and commercial documents. The solution had to keep those documents in-region and off the public internet, with encryption and least-privilege access throughout.

Solution

The solution was delivered in two phases, both orchestrated end to end by a single AWS Step Functions state machine so that every case follows an auditable, retryable path.

~100

Inbound claims per month the pipeline is sized to process (projected volume)

2

Stage AI pipeline: fast triage followed by deep cross-document analysis

11

Purpose-built Lambda functions orchestrated end to end by Step Functions

By the numbers:

  • ~100 - Inbound claims per month the pipeline is sized to process (projected volume)
  • 2 - Stage AI pipeline: fast triage followed by deep cross-document analysis
  • 11 - Purpose-built Lambda functions orchestrated end to end by Step Functions
Changes

The engagement delivered the end-to-end pipeline defined in the project success criteria: automated email intake, Stage 1 triage, Stage 2 deep analysis, a draft funding memorandum in the client's house template, and a secure reviewer interface, all deployed into the client's AWS environment. Acceptance was based on demonstrating that the system can ingest a claim email, run both stages end to end, produce a draft memorandum and surface the case for underwriter review.

  • Zero-touch intakeExisting email submissions become the system entry point via Amazon SES and S3, with no manual upload required of the client's staff.
  • Automated Stage 1 triageEach claim is screened against the client's hard-no criteria, combining model-based classification with deterministic numeric checks, and given a verdict with full rationale.
  • Deep Stage 2 analysisPer-document reasoning and cross-document synthesis produce a recommendation, confidence score, funding envelope, identified risks and red-flag findings.
  • Draft memorandum, human decisionA first-draft funding memorandum is assembled into the client's house template, ready for underwriter amendment, with the final fund or no-fund decision left firmly with the client.
  • Auditable and secure by designA full audit trail is captured in DynamoDB, documents stay in-region behind VPC endpoints with KMS encryption, and Bedrock Guardrails defend against prompt injection.
  • HandoverThe system was delivered as a single AWS SAM template with a demonstration and documentation so the client can operate and extend it.

With an auditable, human-in-the-loop foundation in place, the client is positioned to process more applications with the same underwriting team and to extend the pipeline, including deeper integration with its de the platform case management system, as demand grows.

AWS Stack

Amazon SES

For zero-touch email intake and outbound requests for further information.

Amazon Textract

For accurate text and table extraction from claim documents.

Amazon Bedrock

With Claude Haiku 4.5 and Claude Opus 4.7, plus Bedrock Guardrails, for staged triage, deep analysis and prompt-injection defence.

AWS Step Functions

For auditable, retryable orchestration of the entire pipeline.

AWS Lambda

For the pipeline and API compute running inside a private VPC.

Amazon DynamoDB

For case state, status tracking and the full decision audit trail.

Amazon S3

And AWS KMS for encrypted, in-region document and memorandum storage.

YOU MIGHT LIKE

Related success stories

View all case studies

Case Studies | Insights

Utilising Language Recognition, Speed, and Enhanced Security to Make Social Media a Force for Good

  • Here, we take a detailed look at how the Cloud Combinator team collaborated with another cutting-edge AI service provider that provides intelligent systems to “make social media more social” for brands and users alike.
  • Arwen AI is a UK-based startup specialising in AI solutions to manage and enhance brands’ social media interactions. Founded in 2020 by Matt McGrory, Dr. David Cole, and Joel Bailey, Arwen. AI focuses on using AI to automatically detect and remove spam, toxic comments, and other unwanted content from social media platforms.
  • The team at Arwen have three core products. ‘Moderate’ is focused on identifying and removing toxic content from social media channels. ‘Engage’ helps brands identify and engage with meaningful conversations on social media, and ‘Customize’ allows brands to apply bespoke algorithms to their channels - creating an even more effective moderation and engagement.
Read more
CONTACT US

Ready to turn AI into impact?

We'll help you spot the highest-value opportunities, reduce risk around your first AI initiative, and define a clear path to results from day one.

Why talk to us:

Outcome-driven recommendations

AWS-recognised delivery expertise

Risk-aware AI adoption

Clear next step, not a sales pitch

Start with a focused 20-minute conversation about your goals — no pressure, no commitment.

This website uses cookies to enhance user experience and to analyze performance and traffic on our website.

See our Privacy Policy for details.