RAG assistants
Chatbots that search your documents and answer with sources.
AI Chatbots & Conversational AI
AI chatbots that answer from your data — and know when to hand over
Customer-facing and internal assistants built on large language models, grounded in your own content and connected to your systems, with guardrails, source citations and a clear path to a human.
In short
How do you build an AI chatbot that gives accurate answers?
An accurate AI chatbot answers from your own content rather than from the model's memory. ImliStack builds retrieval-augmented generation (RAG) assistants that search your documents, products or database, answer with citations, refuse out-of-scope questions, log every conversation and hand over to a person when confidence is low. Connected tools let the bot look up orders, book slots or create tickets.
Where we usually help
- Support teams answer the same questions from many documents
- Customers need answers outside office hours
- Staff need a natural-language way to query internal data
- A chatbot demo impressed people but cannot be trusted in production
What we deliver
AI Chatbots & Conversational AI capabilities
Natural-language data access
Ask questions of your database in plain language with safe, read-only queries.
Tool-connected bots
Look up orders, create tickets, book appointments or update records through your APIs.
Web, mobile and in-app chat
Chat interfaces for your website, Android and iOS apps, with real-time streaming.
Guardrails and handover
Topic limits, tone rules, escalation to a human and conversation logs.
Evaluation
Test sets of real questions to measure accuracy before and after launch.
How we work
A delivery approach you can follow
Written plans, visible progress and decisions recorded as we go — so nothing depends on memory.
Collect the questions
Gather real questions and the documents that answer them.
Ground the bot
Index your content and connect the systems it needs.
Test on real queries
Measure answer quality and fix gaps before launch.
Launch and improve
Monitor conversations, fix failures and expand scope gradually.
Technology
Tools we use for ai chatbots & conversational ai
We choose tools for your constraints, not our habits. See the full technology overview.
Proof, not promises
We built AnywhereGPT, an Android assistant that brings an LLM chatbot into any app, a natural-language MySQL assistant, and Python and LangChain services for AI-generated insights.
See AI buildsFAQ
AI Chatbots & Conversational AI: common questions
How do you stop a chatbot from making things up?
By grounding it in your content with retrieval, requiring citations, limiting its scope, testing it on real questions and logging every conversation so failures are found and fixed.
Can the chatbot connect to our systems?
Yes. It can call your APIs to look up orders, create tickets or book appointments, with permissions limited to what the bot needs.
Which channels can it run on?
We build web chat and chat inside Android and iOS apps, and can integrate with messaging channels that provide official APIs.
Next step
Have a product to build or a system to fix?
Tell us what you are working on. You will get a considered reply from an engineer — with questions, a suggested approach or an honest “we are not the right fit”.