Agent Strategy
You know AI agents are the move. You don't know which workflows to target first. We run sprints against your real data and tell you exactly where agents will deliver.
Read moreAgent type
Knowledge agents that cite their sources
Your team has the data — in wikis, drives, ticketing systems, data warehouses. They can't find it fast enough. Knowledge agents retrieve, ground, cite, and synthesize across your entire knowledge surface. We design them, build them, and run them in production.
Trusted by teams building and running mission-critical platforms
Challenges
The challenge with the status quo
Your data isn't the problem — your team's ability to find and trust it is. Wikis go stale. SharePoint becomes a graveyard. Even when the answer exists, no one finds it in time. Generic LLMs hallucinate. The fix isn't more data — it's grounding the agent in yours, with provenance.
Knowledge sits in five-plus systems your team has to search separately
01Generic AI tools hallucinate on domain-specific questions
02Documents go stale — agents need to know what to trust
03Compliance and legal need every answer cited and auditable
04Approach
How we deliver in production
How knowledge agents get built, from mapping the work through to running them in production.
01
Knowledge mapping
We audit your knowledge surface — wikis, drives, ticketing systems, data warehouse, internal apps. We figure out what to ground the agent in, and what to leave out.
02
Retrieval architecture
We design the retrieval pipeline: chunking, embeddings, hybrid search, rerankers. Tuned to how your team actually asks questions.
03
Production engineering
We build the agent on Azure, .NET, and Semantic Kernel — wired into your auth, your data, your audit log. Citations and confidence scores from day one.
04
Governance & tuning
We monitor what's being asked, what's being cited, and what's drifting. We update the corpus and retrieval params as your knowledge evolves.
Outcomes
What you get
Typical ranges for grounded retrieval in production.
Share of answers that cite the correct source document
95%+
citation accuracy
Typical improvement vs. existing search across your knowledge surfaces
3-5x
faster retrieval
When the agent doesn't know, it says so. No hallucinations on grounded queries.
0
made-up answers
Capabilities
What we deliver
What knowledge agents do in practice, and what you can hold us to.
01
Hybrid Retrieval
Vector search + keyword + reranking. The right answer doesn't always live in the most semantically similar chunk — we tune for what works on your data.
02
Citation-First Design
Every answer comes with the source — links, page numbers, paragraph anchors. Auditable by default.
03
Permission-Aware
Agents respect your existing access controls. Users only retrieve from documents they're allowed to see.
04
Multi-Source Synthesis
Agents pull from multiple systems in a single query — wiki, SharePoint, Salesforce, data warehouse — and synthesize the answer.
05
Freshness Tracking
Agents know when a document is stale. They flag outdated answers and route to a human SME when confidence drops.
06
Domain Tuning
Embeddings, prompts, and retrieval params tuned to your domain vocabulary — not generic web language.
How to get one
The engagements that build knowledge agents
Most knowledge agents engagements start with strategy, move through engineering, and end up in operations. Pick where you are.
Start here
Bring us your documentation
Wherever the answers actually live — wikis, PDFs, ticket history, someone’s head. We will tell you what it takes to get cited answers out of it.