Bots that know your data -- and take action.
Domain-trained chatbots and agents for market research, sales, support, HR, and legal. With source citations, audit trail, and system integration -- as a standard cloud module or custom-built agent.
Three reasons 80% of bot pilot projects stall.
We have been building agents in regulated industries since 2022. The patterns that cause projects to fail are always the same -- and they almost never have to do with the underlying model.
Off-the-shelf bots do not know your data.
Generic AI tools answer generically -- tariff sheets, contract clauses, code frames are not in the models. Hallucinated answers cost more than they save.
RAG is curation, not plug-and-play.
Only a clean knowledge base turns an LLM into a reliable agent. Chunking, retrieval, re-ranking, source citations -- that is engineering work, not a prompt.
Compliance stalls pilot projects.
Data protection clearance, audit logs, source evidence, on-prem option. If you do not plan for this from day one, you fail at the first security review.
Six building blocks that separate a pilot from a product.
In every bot project we combine the same capabilities -- as standard modules in deepsight cloud or custom-built in individual projects.
Answers with Source Citation
Every statement links back to the original -- tariff sheet, contract clause, study. No hallucinating without evidence.
Tool Use & Actions
Agents read from CRM, write to Jira, generate quotes, trigger workflows. Function calling used productively.
RAG Over Your Knowledge Base
PDFs, SharePoint, Confluence, databases. Versioned, with re-ranking and permissions at document level.
Guardrails & Audit Trail
Topic filters, prompt injection protection, complete logging. Who asked what, what the bot saw, what it answered.
Multilingual
DE, EN, FR, ES, IT, NL, PL, TR -- the bot answers in the language of the question. Codebooks and sources remain multilingual.
Human-in-the-Loop
Escalation to domain experts with one click. Bot learns from every override -- feedback flows back into the code frame.
How a deepsight agent answers a question.
Four stages, always in the same order. What changes from project to project are the data sources, tools, and depth of guardrails -- not the architecture.
Knowledge Base
Consolidate documents, databases, APIs. Chunking, embedding, versioned. Permissions per source.
Retrieval
Hybrid search, re-ranking, filtering. For every query, relevant sources are returned with a score.
Tools & Model
LLM makes the decision, calls tools (CRM, Jira, custom APIs). Multi-step agents with plan-and-act.
Guardrails
Topic filters, PII scrubbing, audit log. Before delivery, every answer is checked against policies.
Configure or build -- depending on your data.
Standard scenarios run as a module in deepsight cloud. As soon as custom tools, exotic data sources, or on-prem are needed, our custom team takes over.
Configure instead of develop.
Upload your knowledge base, define guardrails and tone-of-voice, go live in two weeks. For knowledge bots, support triage, HR FAQ, open-end coding bots.
- Wizard for knowledge base upload (PDF, Confluence, SharePoint)
- Pre-built templates for 6 standard scenarios
- Audit trail, permissions, multilingual natively
- Per conversation or flat rate billing
When standard reaches its limits.
Sales bot that writes to CRM. Contract analysis with custom schema. Research agent with custom methodology. On-prem or VPC, custom model, exotic data sources.
- Discovery, build, run -- one SLA, one team
- Tool integration with CRM, ERP, custom APIs
- On-prem, VPC, or hybrid - custom models possible
- Handover to maintenance or continuous operation
Domain Agent. Not ChatGPT Plugin.
Generic bot platforms are quick to set up -- and just as quick to shut down because compliance, source citations, or tool integration are missing. Three properties that set us apart:
- Sources, not hallucinations. Every statement shows original document and location. When uncertain, the bot escalates -- it does not guess.
- Actions, not just answers. Tool use is first class -- the bot reads, writes, and triggers in your systems.
- Audit-proof from day 1. EU hosting, DPA, logs per conversation. You can give data protection and audit the answer.
What else belongs to the solution.
Bots rarely run alone -- they sit on a knowledge base, a tracking setup, or a custom platform. Here are the neighbors.
Standard bots as a module -- RAG bot, coding bot, knowledge bot. Live in two weeks.
Turn chatbot analysis results into presentations automatically -- on-brand, ready to share.
Custom agents with tool integration, custom models, on-prem -- when standard is not enough.
Structured fields from documents -- often the precursor to contract or sales agents.
Bring us three typical questions your users ask.
We look at the data, sketch the knowledge base live, and tell you honestly whether cloud standard is enough or if it needs a custom project. No sales machine.