What this solves
11
AI tools built for your context — not the internet's.
Generic AI tools give generic answers. Internal tools trained on your data, your processes, and your voice give answers your team can actually use.
Get a quote Typical timeline: 3–8 wks
Process
How it works
01
Discover & Map
We audit your current processes and identify the highest-impact automation opportunities.
02
Design & Build
The gap between a generic ChatGPT wrapper and a genuinely useful internal AI tool is the data and context layer.
03
Monitor & Optimise
Your automation ships with monitoring, alerting, and a handover pack. We stay available for optimisation.
What's included
The gap between a generic ChatGPT wrapper and a genuinely useful internal AI tool is the data and context layer. We build internal tools that connect to your actual data — your documents, your CRM, your knowledge base, your runbooks — via RAG pipelines backed by vector search. The result is AI that knows your company, your products, your clients, and your tone of voice. Common deliverables include internal knowledge assistants, contract review tools, meeting summary systems, proposal drafting tools, and analysis co-pilots that ground outputs in your specific data rather than internet generalities.
What you receive
- Data ingestion and chunking pipeline for your documents, PDFs, wikis, and CRM records
- Vector database setup and embedding pipeline (Pinecone, Weaviate, or pgvector depending on data volume and query pattern)
- Custom retrieval strategy — hybrid dense/sparse search with metadata filters for accurate, in-scope results
- Production-grade internal web application with your branding, RBAC, and single sign-on
- Prompt architecture documentation — system prompts, persona configuration, and guardrail rules
- Admin panel for managing knowledge base ingestion, monitoring usage, and reviewing conversation logs
- Evaluation report — benchmarked accuracy on 50 representative queries before handover
Typical outcomes
- Research and briefing tasks completed in 5–10 minutes that previously took 2–3 hours of manual work
- Consistent, on-brand outputs for repetitive content tasks (proposals, reports, client communications)
- New staff onboarding accelerated — AI assistant answers process questions instantly, reducing senior staff interruption load
- Institutional knowledge made searchable — documents that no one reads become queryable
- Accurate, source-cited answers with clickable references so your team can verify before acting
- Guardrails enforced — tool only operates within defined scopes and escalates to humans outside its confidence range
Technology we use
Ready to discuss your project?
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Tools & integrations we work with
OpenAI GPT-4oAnthropic ClaudeLangChainPineconepgvectorReactFastAPIAzure OpenAISupabaseAuth0
We integrate with your existing stack — no rip-and-replace required.
Questions
Common questions about Internal AI Tools.
RAG (Retrieval-Augmented Generation) grounds every response in documents retrieved from your knowledge base. The model is instructed to only answer from retrieved context and to state when it doesn't have enough information rather than speculate. We also include citations — every factual claim links back to the source document so your team can verify. In our evals, well-designed RAG pipelines reduce hallucination rates from ~30% (ungrounded) to under 3%.
Yes. We build ingestion pipelines for all major formats and sources — PDFs (including scanned documents via OCR), DOCX, SharePoint, Confluence, Notion, Google Drive, and database exports. The ingestion pipeline handles chunking, cleaning, embedding, and indexing.
Every internal tool we build includes role-based access control. Common patterns: all staff can query general company knowledge, only the legal team can query contracts, only sales can query client records. We integrate with your existing identity provider (Azure AD, Google Workspace, Okta) via SSO so there's no separate user management.
We build the ingestion pipeline to run on a schedule — daily or hourly depending on how frequently your documents change. When a document is updated in SharePoint or Confluence, it's automatically re-chunked, re-embedded, and the old version is retired. The admin panel gives your team visibility into what's indexed and when it was last updated.
Yes — we can build agentic functionality on top of the knowledge assistant. Common additions: draft a response (to an email or RFP) and send it for human approval, create a CRM record from a conversation summary, or trigger a workflow based on a specific intent detected in the query. This turns the tool from a lookup assistant into an operational co-pilot.