Document and knowledge automation
Document and knowledge automation uses AI agents to read your documents, pull out the facts that matter, check them against your rules, and answer questions from your own knowledge with the source attached. The answers are grounded in your documents and cite where each one came from, and a person signs off where the stakes are high. Softblues builds these systems in production, connected to the document stores you already use. Your data stays in your environment.
The answer is in your documents. Finding it is the job.
The facts your team needs are buried across contracts, forms, emails and policy, read by hand, one document at a time. It is slow, it is inconsistent, and the same questions get asked of the same files every week. Reading the documents, checking them against your rules and answering with the source attached is what gives that time back.
What can we automate?
Reading, checking and answering from your own documents, with a citation and a person on the high-stakes calls.
Extract and structure data
Pull names, dates, amounts and clauses out of contracts, forms and records, and write them into your systems as clean, structured fields.
- Names, dates, amounts and clauses pulled out
- From contracts, forms and records
- Written into your systems as clean fields
Check documents against rules
Run each document against your policy or regulatory rules and flag what does not match, with the relevant clause attached for a person to confirm.
- Each document run against your policy
- What does not match is flagged
- With the relevant clause attached
Answer from your own knowledge
Ask a question in plain English and get an answer drawn only from your documents, with a citation to the source so the reader can verify it.
- Ask a question in plain English
- Answers drawn only from your documents
- A citation to the source on every answer
Keep an audit trail
Log what the system read, what it found and what was decided, so you can show how any answer was reached.
- What the system read
- What it found
- What was decided, all logged
How a document automation build works
Three steps, connected to your document stores, with your data kept in your environment.
Process Discovery
A short, paid engagement that maps the documents, the questions and the accuracy you need.
- We map the documents and the questions
- We prove accuracy on your own files
- You get a fixed-price plan with the payback line
The build
Built connected to SharePoint, Drive or your DMS, with your data kept in your own environment.
- Connected to your document stores
- Your data stays in your environment
- A person signs off high-stakes outputs
Run it
It goes live with citations and an audit trail on every answer, plus monitoring.
- Evals and monitoring in place
- Citations and an audit trail on every answer
- Money back if the proof of concept fails
Where this has been built
Designed pre-discoveryCompliance file review (financial advice, anonymised)
A four-stage system that reads each client file, checks it against the rules, and routes it to an adviser for sign-off, designed to run in the client's own environment.
In production (beta)Clinical research synthesis (Lumono.ai)
A pipeline that turns scattered evidence into a structured, publication-ready synthesis, with the sources attached and an expert reviewing the output.
What does it cost?
Fixed price, quoted after a paid Process Discovery, with a payback line so you know when the investment returns. As a rule of thumb, a £20,000 build that saves £4,000 a month pays back in about five months.
Estimate your savingDocument and knowledge automation: at a glance
- What
- AI agents that read your documents, check them against your rules, and answer from your knowledge with citations.
- For
- Teams with a heavy documentation load and knowledge spread across systems, especially regulated professional services.
- Workflows
- Extract and structure data, check against rules, answer from your knowledge, keep an audit trail.
- How
- Paid Process Discovery, fixed-price build connected to your document stores, then evals, monitoring and an SLA.
- Accuracy
- Answers are grounded in your documents and cite their source; a person signs off high-stakes outputs.
- Delivery
- Production in 90 days, fixed price, money back if the proof of concept fails. Your data stays in your environment.
- Proof
- Softblues runs its own company on six connected Claude agents; 50+ AI projects delivered.
- Based in
- London-based, working with mid-market firms.
Common questions about document automation
Does it make things up? How do you handle hallucination?
Answers are grounded in your own documents and cite the source, so a reader can check each one against the original. Where the stakes are high, a person reviews the output before it is acted on. The system is built to say when it cannot find an answer rather than guess.
Where does our data live?
In your environment. We connect to the document stores you already run, and the documents and the processing stay on the platform you control. We do not move your data to ours.
Which document systems do you connect to?
SharePoint, Google Drive, and common document management systems, plus email and shared drives, through native connectors or a custom integration with proper authentication and audit logging.
How accurate is the extraction?
It depends on the documents and the rules, which is why we scope it in Process Discovery and prove it on your own files before the full build. Where accuracy matters most, a person confirms the output, and the audit trail records what was checked.
How long until it is live?
Production in 90 days is the standard. Discovery is short, typically one to two weeks; the build timeline is fixed in the discovery plan.
How do you keep our data secure?
Builds run with role-based access, audit logging and data handling built around ISO 27001 principles, in your own environment. We are a registered partner across Anthropic, Google Cloud and Microsoft, so we meet you on your stack.
Scope your document automation
Start with a paid Process Discovery. We map the documents and the questions, prove accuracy on your own files, and come back with a fixed-price build that keeps your data in your environment.