Services · Last updated June 2026

Make your scattered knowledge usable

Blash AI is the artificial-intelligence division of Blash Advisory, a London-headquartered corporate finance and advisory firm specialising in retrieval augmented generation and knowledge systems, serving operators, corporates and funds across the UK, EMEA and the Far East.

We connect language models to your private documents, policies and data, so your team gets accurate answers with citations rather than hunting through folders.

Up to 25 hrs saved per case where firms put knowledge behind retrieval Sector benchmarks
Every answer cited back to the source document
Permissioned so people see only what they should
What we build
  • Ingestion of your documents, policies and data
  • Hybrid retrieval tuned to your content
  • Answers with citations back to the source
  • Permissioning so people see only what they should
  • Evaluation so accuracy is measured, not assumed
Why it matters

A model that cannot cite its source is a liability in a regulated business. We build retrieval that grounds every answer in your documents and shows where it came from, so the output can be trusted and checked.

  • Accurate answers grounded in your own content
  • Citations to the source for every answer
  • Permissions that respect who can see what
What we install first

The workflows we automate first

We name the workflow rather than sell a model. These are the jobs that pay back first.

  • An internal policy assistant with citations
  • Knowledge search across your document estate
  • Contract and report question-answering
  • Onboarding and procedure lookup
  • Support answers grounded in approved content
  • Accuracy measured with evals before go-live
How it actually works

We ingest your content, build retrieval that matches how your documents are written, and require the system to cite its sources. Permissions are enforced so a user only retrieves what they are entitled to see, and evals measure answer accuracy against a known set before go-live.

Built to be governed

Source citations make every answer checkable. Permissions are enforced at retrieval, sensitive content is handled to your policy, and accuracy is measured and reportable. This is retrieval a compliance team can stand behind.

Our method

The Blash Grounded-Retrieval Method

  1. Ingest and structure your private content
  2. Tune hybrid retrieval to your documents
  3. Require citations to the source on every answer
  4. Enforce permissions and measure accuracy with evals
Proof

Where this has paid back

Accountancy

Removing repetitive client-chasing from an accountancy practice

Client chasing became systematic, and month-end blockers were visible early enough to act on them.

85%fewer manual chaser emails drafted by staff
4 working daysearlier visibility of missing documents before month end
Legal services

Structured matter intake for a law firm

Fee-earners received cleaner intake packs while legal judgement stayed with the lawyer.

72%fewer incomplete intake packs
90 minutesaverage time to first internal summary, down from 24 hours
Legal services

Building matter chronologies from unstructured documents

Matter files became easier to review and chronology preparation moved from manual drafting to exception checking.

80%documents classified before paralegal review
4 hoursfirst chronology draft, down from roughly 2 days
See all proof →
Questions about knowledge and RAG
What is RAG, in plain terms?

Retrieval augmented generation. The model answers using your documents, fetched at the moment of the question, and cites where each answer came from, rather than relying on what it was trained on.

How do you stop it making things up?

Answers are grounded in retrieved content and must cite the source. Where the documents do not support an answer, the system says so rather than guess, and accuracy is measured with evals.

Can it respect who is allowed to see what?

Yes. Permissions are enforced at retrieval, so a user only ever sees answers drawn from content they are entitled to access.

What content can it use?

Contracts, policies, reports, knowledge bases, manuals and structured data. We tune retrieval to how your specific content is written.

Ready to build this?

Book a call and we will map the first workflow worth automating

Book an AI audit
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