Internal Knowledge Base AI Assistants (RAG Systems)
Make your company knowledge searchable in plain language.
Why this service
Company knowledge is useless if no one can find it. A RAG system makes documents, manuals and internal threads searchable in natural language — without data leaving your environment.
What you concretely get
Every phase of the engagement produces a written or systemic deliverable. No slide-deck show, no promised "later".
Discovery report
Current state, bottlenecks, baseline metrics and a concrete proposed focus. 12–18 pages, written.
Architecture diagram
Technical design: model choices, data flow, integration points, security. Readable and reviewable.
Working production system
Deployed system in your environment — not a demo. Source code and configurations are handed over.
Runbook and documentation
User guide, maintenance procedures, failure-mode checklist, escalation paths. Finnish/English.
Adoption programme
User training per role, internal "AI champion" coaching, 30/60/90-day milestones.
Outcome reports
Monthly: where metrics have moved against the baseline, what adjustments come next month.
How we measure success
Metrics are agreed at discovery and the baseline is captured before implementation. These are the numbers we discuss at the 30/60/90-day check-ins.
- Time-to-answer
- Answer relevance (1–5 user rating)
- Source-citation accuracy
- Knowledge-base coverage by topic
- Expert-escalation count
- Weekly query volume (a proxy for user trust)
Use cases
Internal knowledge assistant
Query HR, IT or product info in plain language.
Technical docs
Engineers find answers in thousands of pages in seconds.
Customer portal
Scoped search experience for customers in their own docs.
Compliance search
Statutes and internal policy side by side.
Sales enablement
Pitches, comp comparisons and messaging in one search.
Onboarding search
New hires reach company knowledge quickly.
Our delivery process
Discovery
We map the current state, processes and biggest productivity leaks.
Use case selection
We prioritise the highest-value, lowest-risk combinations.
Pilot
We build a working version in 4–6 weeks, with metrics.
Roll-out
We harden it for production and integrate the SaaS stack.
Training
Hands-on workshops and an internal champion for the team.
Optimisation
We measure, tune and scale — AI keeps living.
Technologies used
Frequently asked questions
A typical pilot completes in 4–6 weeks, with full production use in 2–3 months. We give a concrete timeline after the discovery call.
We design the architecture so your data stays under your control. We support self-hosted models and EU-region cloud, GDPR-aligned.
No. We build on top of your existing SaaS stack — we connect them, we don't replace them.
Adoption is part of every engagement. Without it, AI doesn't produce results — and that's already priced in.
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Learn more →Ready to get this in production?
We always start with a free 30-minute discovery call. No sales pressure.
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