From pilots to everyday work

Many organizations have tried AI in pockets — a chatbot here, a few licences there — without changing how work actually gets done. The gap is integration: AI that can’t see your documents, your customers or your case history can only offer generic help.

We connect AI to the systems that hold your knowledge and run your processes, so it can answer with your information and act within your workflows.

Without losing control

Enterprise integration has to respect the controls you already have. People should only get answers from content they’re allowed to see; actions should follow your approval rules; and every request should be traceable.

We design integrations with your IT and security teams from the start, using your identity provider, your cloud and your policies.

How a knowledge assistant works

Your content

  • SharePoint & file shares
  • Intranet & wikis
  • CRM & case history
  • Databases
Kept up to date

Indexing

  • Extract & splitText from files and records
  • Embed & indexVector and keyword search
  • Permissions syncedWho may see each source
Permission-aware search

Assistant

  • RetrieveOnly sources this user may see
  • AnswerGrounded in those sources
  • CiteLinks back to the originals
Answers with sources

Your people

  • Microsoft Teams
  • Web or intranet
  • Inside your apps
Throughout
  • Single sign-on
  • Audit log
  • Data stays in your cloud
  • Quality evaluation
Retrieval-augmented generation (RAG): content is indexed with its permissions, so each person only gets answers from what they’re allowed to see.

Where we integrate AI

  • Knowledge assistants

    Answers from your documents, intranet and policies — respecting who is allowed to see what.

  • Collaboration tools

    AI where people already work: Microsoft 365 and Teams, Slack and Google Workspace.

  • CRM & service desk

    Salesforce, HubSpot, Dynamics 365, Zendesk and Freshdesk — summaries, drafting, triage and next steps.

  • Workflow automation & agents

    Multi-step processes that combine AI with approvals, so routine work moves faster and people decide.

  • Documents & forms

    Extraction and classification feeding straight into the systems that need the data.

  • Your own systems

    Line-of-business and legacy applications connected through APIs and secure MCP servers.

Agents with a human in the loop

For processes — not just questions — we build agents that do the legwork and let people make the decisions.

Trigger

  • New ticket, form or email
  • Scheduled task
Starts

AI agent

  • Gathers contextFrom the systems it may use
  • Drafts the outcomeReply, record, recommendation
Proposes

Person

  • Reviews & approvesOr edits and sends back
Approved

Systems

  • Record updated
  • Action logged
The agent prepares the work; a person approves anything that changes data or reaches a customer.

Enterprise governance, built in

  • Identity & access

    Single sign-on and role-based permissions, checked on every request.

  • Data protection

    Redaction of sensitive fields, data kept in your cloud and region, and AI services configured not to train on your data.

  • Human in the loop

    Approval steps for any action that changes data or reaches customers.

  • Audit & monitoring

    Logs of every request and action, quality reviews of real conversations, and usage limits.

  • Evaluation

    Test sets and checks that measure answer quality before and after every change.

  • Policy & training

    Practical AI usage policies and training, so staff use the tools well and safely.

Measuring success

Every rollout starts with agreed measures, tracked from the pilot onwards, so decisions to scale are based on evidence:

  • Adoption

    Who uses it, how often, and for which tasks.

  • Time saved

    Measured against how the same work was done before.

  • Answer quality

    Accuracy on test sets and on reviewed real conversations.

  • Risk

    Escalations, blocked actions and data-protection events.

From pilot to organization-wide

  1. Discovery

    Find the processes where AI will save the most time, and the systems involved.

  2. Architecture

    Design the integration, permissions and data flows with your IT and security teams.

  3. Pilot

    Roll out to one team, measure the results and refine.

  4. Scale

    Extend to more teams and systems on the same governed foundation.

  5. Support

    Ongoing monitoring, updates and improvements.

Related: Knowledge Base & RAG builds the company-wide knowledge base behind these assistants, Custom MCP Servers connect your systems to Claude, ChatGPT and Gemini, and Private AI Cloud covers isolated AI environments in your own cloud account.

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