Serge BelovAI Knowledge Agents
Give your team an AI assistant that actually knows your business.
What this is
Generic AI assistants don't know your company. I build custom AI knowledge agents trained on your documentation, SOPs, wikis, and internal knowledge — so your team gets accurate, context-aware answers instead of having to dig through Confluence or ask a senior person.
Who it's for
- Teams with large documentation bases that nobody reads
- Companies where onboarding is slow because knowledge is scattered
- Customer support teams drowning in repetitive questions
- Organizations with critical tribal knowledge locked in senior employees' heads
Problems it solves
- New hires take weeks to get up to speed because they can't find anything
- The same questions get asked over and over to the same people
- Important documentation exists but nobody knows where or how to search it
- Customer support can't answer questions without escalating constantly
What you get
- Deployed AI knowledge agent connected to your data sources
- Web-based chat interface (or Slack/Teams integration)
- Admin panel to manage knowledge sources and monitor usage
- Source citation on every answer so users can verify
- Usage analytics dashboard
- Two weeks of post-launch tuning and support
How it works
- 1
Knowledge audit
We inventory your knowledge sources: wikis, PDFs, SOPs, databases, and identify what's worth indexing.
- 2
Architecture
I design the retrieval system, embedding strategy, and interface — optimized for your use case.
- 3
Ingestion
Your content is processed, chunked, embedded, and indexed. I test retrieval accuracy extensively.
- 4
Build interface
The chat UI and admin panel are built and connected. Slack or Teams integration if needed.
- 5
Test & tune
Real-world testing with your team. I tune prompts and retrieval until answers are accurate and reliable.
- 6
Deploy
Production deployment with monitoring. Two weeks of active support and tuning post-launch.
Pricing
From $2,000
Final price depends on scope. We agree on a fixed cost before any work starts.
Optional add-ons
Slack or Teams integration
Direct integration so your team can query the agent without leaving their communication tool.
Additional data source
Connect additional knowledge sources: Notion, Confluence, Google Drive, PDFs, or custom databases.
Custom branded UI
A fully custom chat interface matching your brand, beyond the standard template.
Ongoing knowledge management
Monthly re-indexing as your docs change, prompt tuning, and quality monitoring.
Frequently asked questions
What data can the agent use?
Notion pages, Confluence, Google Docs/Drive, PDFs, Markdown files, web pages, and structured databases. Most text-based knowledge sources can be ingested.
How accurate are the answers?
Accuracy depends on the quality of your source material. With well-maintained documentation, the agent answers correctly 85–95% of the time. Every answer includes source citations so users can verify.
Is my data private?
Yes. Your documents are processed and stored in your own infrastructure (or a private cloud environment). Nothing is shared with third parties beyond the LLM API call, which is covered by enterprise data agreements.
What AI model does it use?
Claude by Anthropic by default — it excels at grounded, citation-heavy responses. I can also use GPT-4 or open-source models depending on your privacy requirements.
What happens when our documentation changes?
The ongoing knowledge management retainer handles re-indexing. Without it, I can do periodic re-indexing at an hourly rate, or I can set up automated re-indexing as part of the initial build.
Ready to get started?
Describe your situation and I'll tell you exactly how I can help — or be straight with you if I'm not the right fit.