Finabeo RAG Agent: Instant Answers From Company and Cloud Knowledge
A retrieval-augmented generation system trained on Finabeo's own documents, case studies and the major cloud providers' documentation, giving fast, attributable answers for consulting and marketing work.
Company Overview
Finabeo is a UK-based FinOps and AI consultancy working with global enterprises, and its consultants and marketers draw constantly on a large body of internal material and vendor documentation.
That knowledge lived in scattered folders and supplier docs, so people lost time finding the right detail and sometimes reused text that was out of date, which is exactly the kind of friction this build set out to remove.
Problem Statement
Knowledge lived in scattered folders and vendor docs, so people lost time finding the right detail or reused outdated text. For a consultancy whose value is the accuracy of its advice, that is a quiet but real risk to quality and speed.
Outcome Delivered
The RAG agent became the fastest way to find and reuse accurate knowledge inside Finabeo, resolving internal queries faster, putting correct references into proposal drafts, helping marketing verify claims, and getting new hires up to speed sooner, all with sources attached so every client-facing piece can be trusted.
Executive Overview
Teams spent less time searching and produced more accurate drafts and client responses, and marketing used the same agent to verify claims in posts and blogs. Internal queries resolved faster, proposal drafts carried correct references, and new hires onboarded more quickly by self-serving answers to common questions.
In short, the RAG agent became the fastest way to find and reuse accurate knowledge inside Finabeo, which lifted delivery speed and confidence in every client-facing piece of work.
Our Approach
We built a private RAG stack, RAG meaning retrieval-augmented generation, an approach where the AI looks up trusted source documents first and then answers from them, so responses are grounded rather than invented. It ingests company content and selected cloud documentation, normalises it, and serves precise answers with citations.
We audited the content types, set ingestion rules, and tuned retrieval for jargon-heavy queries, then added guardrails for style and a feedback loop to improve recall and precision over time, so the agent supports project work, proposals and content creation by grounding everything in trusted sources.
Challenges
Challenges Faced
Every engagement starts with a clear-eyed view of what was actually getting in the way, because you cannot fix what you cannot see. Here we set out the real constraints the client was working within, the costs and risks they were carrying, and the gaps that needed closing before any meaningful progress could be made.
Let's Transform Your Enterprise Today
Send an EnquiryKnowledge scattered across sources
Material was spread across folders and vendor docs with no single place to look.
Time lost searching
People spent meaningful time hunting for the right detail before they could act on it.
Outdated text reused
Out-of-date text was sometimes reused because the current version was hard to find.
Accuracy risk in client work
Inconsistent answers carried a quiet risk to the quality of client-facing work.
Deployed solutions
What We Did
A look at how we approached the work, from the first discovery sessions through to the changes we put in place, and the thinking behind each decision along the way. The aim is always the same, to deliver something measurable that the client owns and can build on, rather than a one-off fix that fades once we leave.
Unified corpus
It brings Finabeo's documents, case studies and selected cloud-provider references into a single searchable layer.
Precise retrieval
It retrieves the right passage rather than the whole document, and cites it, so answers are sharp and checkable.
Attribution by default
Every answer includes its sources, so users can verify and reuse it with confidence.
Role-tuned prompts
Different prompt presets handle consultant tasks and marketing tasks, each tuned to its purpose.
Freshness controls
Scheduled re-ingestion keeps vendor changes current, so the agent does not drift out of date.
Access control
Document permissions are respected throughout, keeping sensitive material private.