Expertise / A closer look
AI Assistants & Knowledge Systems
Customer- and team-facing assistants that answer from your own knowledge — with sources, guardrails and a human escape hatch.
The opportunity
Make the next step
a better one.
Buyers and users expect an answer the moment they ask. Support inboxes drown in the same repeated questions, and product, policy and catalogue answers live in documents no one can search in plain language. Assistants change that only when they answer from your content, not from a generic model.
We build the answer surface on your actual content — catalogue, docs, policies and FAQs — with a retrieval pipeline (embeddings + search), citations for every claim, guardrails for out-of-scope questions and a clean handover to a human with full context. We measure deflection and answer quality from day one.
- Working together
- Named delivery lead + team
- Timing
- Prototype in 3–4 weeks; FAQ rollout scoped after
What we deliver
Focused on the right things.
- Commerce and support Q&A over your data
- Retrieval (RAG) pipeline over catalogue, docs and FAQs
- Guardrails, citations and human-escalation states
- Usage analytics and deflection measurement
What you take away
Something you can run.
- Conversation and knowledge map
- Working assistant on your content with sources
- Guardrails, handover and admin controls
- Rollout plan, docs and measurement
Explore the interaction
See a workflow unfold.
A working interface demonstration with sample data. Choose a task, follow its progress and review the proposed result.
See the system
think in steps.
Choose a workflow, inspect the sample input and review the proposed output. You make the final call.
Find inconsistencies in a small sample product catalogue.
Product: Wireless headphones · Category: Audio · Compatibility: missing · Related products use the Headphones category.
- 01Inspect sample product fields
- 02Compare naming and categories
- 03Prepare suggested corrections
Your review workspace.
Run the example to reveal the proposed changes.
This browser simulation demonstrates the workflow and interface. Its sample responses are predefined; it does not call an AI model, access a store or publish changes.
Before we begin
A little clarity
goes a long way.
01What do you need from us to get started?
A short description of the problem, a link to the current website or tool if there is one, and what a useful result would look like. You do not need a finished specification. We agree access, DPA/NDA and content requirements once scope is clear.
02Can you work with what we already have?
Yes. We start from your current setup and constraints. A focused improvement or integration may beat a rebuild — we'll explain options and tradeoffs with costed recommendations before you commit.
03How are cost, timeline and SLAs agreed?
After discovery we issue a scoped proposal: deliverables, milestones, timeline, support and SLA terms. Work begins on sign-off; any change is re-scoped in writing before additional work starts.
Connected expertise