AI Chatbots & Assistants

Customer-facing bots and internal knowledge assistants that actually work.

ServiceLast updated
Service overview

Support automation, internal knowledge assistants, escalation workflows, and chatbots grounded in your real data, not hallucinated answers..

Engagement

What this service includes.

Knowledge base ingestion and RAG setup

Channel deployment and escalation logic

Evaluation harness and tuning

What we offer

Why this service matters.

Grounded answers

Retrieval-augmented generation against your real documents and tickets, with citations and confidence scoring so the bot says I do not know when it should.

Smart escalation

Detects intent, sentiment, and uncertainty, and routes to the right human with context preserved. No more do-loops where the bot loses its place.

Continuous evaluation

Automated test suite of real user questions runs on every change, so we catch regressions before they hit production.

AI Chatbots integrations

Powerful AI integrations.

We pick the right model for your ai chatbots build, then blend providers behind a single internal interface.

OpenAI

GPT and embeddings. Broad ecosystem, strong structured-output and tool use, the safest default for general production.

Claude

Anthropic's frontier model. Our default for agents and long-context work where reasoning matters more than raw speed.

Gemini

Google's long-context multimodal family. Excellent for document and video pipelines, especially at scale.

Grok

xAI's model with live-web reasoning and a different blend of strengths. Useful for research-style and edge-case workloads.

DeepSeek

Open-weight models with strong cost-to-performance. We use it self-hosted when residency or unit economics demand it.

Perplexity

Citation-grounded search API for live-web augmented agents. Drops cleanly into RAG pipelines that need fresh sources.

FAQ

Questions about ai chatbots.

How do you stop the bot from hallucinating?

Retrieval-augmented generation against your real data, hard refusal when no relevant context is found, and a continuous evaluation harness running real questions on every change. Hallucinations are a system design problem, not a model problem.

Can it work on WhatsApp, Slack, our website, all of those?

Yes. We treat the underlying assistant as a service and deploy it to whatever channels matter. The brain is shared, the surfaces are interchangeable.

Where does its knowledge come from?

Your docs, tickets, knowledge base, product data, transcripts. We ingest, chunk, embed, and keep it in sync as your sources change. We do not rely on what the model already knows.

What does ongoing cost look like?

Two parts: model inference per conversation (usually pennies on modern models) and infrastructure for retrieval. We budget both upfront and tune as usage grows.

Get started

Ready to automate your operations?

A 30-minute call to map the highest-impact automation and AI opportunities in your business. You leave with a prioritised list, whether you hire us or not.