GROUNDED · CITED · PERMISSION-AWARE
Ask your company anything, then let it find the answer
Agentic company search that does the work.
Tricky Wombat finds cited answers across Slack, Google Drive, Gmail, and Microsoft 365 — then takes action: schedule the meeting, process the refund, update the ticket. Ask a question; get the answer and the source.



We build AI at every scale
From Large Enterprises

Team Knowledge Discovery
Knowledge lives in your shared drives, chat threads, meeting notes, and scattered docs. Your team is small enough to know the answer exists. But doesn't always know where to find it. Team Knowledge Discovery finds it.
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Enterprise Search
Knowledge lives in every department. Engineering docs, sales playbooks, HR policies, product specs. Your people need answers that cross those boundaries. Connected Search finds them.
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Technical Discovery
Technical knowledge lives across repos, wikis, Confluence, and Slack. API specs, architecture decisions, runbooks, incident history. Your engineers need precise answers that connect those sources. Technical Discovery finds them.
DiscoverIndividuals

Content Creators
You have unique insights, an individual voice, and content that's available everywhere. From YouTube, podcasts, and articles, create a cohesive AI experience for your audience to increase engagement.
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Thought Leaders
Turn books, Substacks, talks, and articles into a searchable knowledge base. Readers get answers from your full body of work — with links back to the source — not inventing what you might have said.
DiscoverContext First
Answer quality is determined before the model generates a single token.
Every major AI model can reason, summarize, and generate. Swap one for another and output quality shifts by single-digit percentages. Change what the model sees before it reasons, and the result changes entirely. Tricky Wombat engineers the full context pipeline: from query intent classification to retrieval, assembly, generation, and evaluation. The model is interchangeable. The pipeline is the product.
- Your question is classified before a single document is retrieved
- Context is assembled for this question, from this user, against this data
- Every answer is scored, cited, and fed back into the pipeline
Classify
Query intent
Retrieve
Hybrid search + rerank
Assemble
Scoped context
Generate
With guardrails
Score
Evaluate + feedback
The model is step 4. The pipeline is the product.
