Custom Chatbots & AI Agents

Support, sales and internal agents that can actually do things — check an order, book a slot, raise a ticket — not just talk about them.

Discuss this See example work

Time to value: Scoped agent in production in 4–6 weeks.
Deployment: Hybrid — sensitive steps can stay on-prem
Category: AI & Intelligent Automation

A woman standing at a desk typing on a laptop

The manual version of this

Invictt AI layer

Define the job

Ground

Give it tools

Contain

Observe

Two support agents wearing headsets in a bright office

Once it's AI-assisted

01/The problem

A chatbot that only answers FAQs is a worse search box, and customers treat it accordingly. Useful agents need to read real records and take real actions, which is exactly the point at which safety, permissions and auditing stop being optional.

02/How it works

The operating model

What enters, what the system does with it, and what reaches you.

System

Define the job

We start from the handful of tasks that carry the volume, not from the full space of things a model could theoretically do.

System

Ground

The agent answers from your documented policy and live records, so pricing, availability and terms are current rather than remembered from training data.

Integration

Give it tools

Scoped, individually-permissioned actions against real systems, with destructive operations behind an explicit confirmation gate.

Check

Contain

Explicit boundaries on what it will never say or promise, plus a clean handover to a human with the full conversation attached.

Check

Observe

Every conversation traced and scored, so you can see resolution rate, escalation reasons, and where it is getting things wrong.

Read the detail behind each stage

Define the job

We start from the handful of tasks that carry the volume, not from the full space of things a model could theoretically do.

Ground

The agent answers from your documented policy and live records, so pricing, availability and terms are current rather than remembered from training data.

Give it tools

Scoped, individually-permissioned actions against real systems, with destructive operations behind an explicit confirmation gate.

Contain

Explicit boundaries on what it will never say or promise, plus a clean handover to a human with the full conversation attached.

Observe

Every conversation traced and scored, so you can see resolution rate, escalation reasons, and where it is getting things wrong.

03/What's included

What you actually receive

Concrete deliverables, not a statement of intent.

Task-scoped agent design grounded in your policy and live data

Permissioned tool access with confirmation gates on writes

Human handover carrying full conversation context

Refusal and escalation boundaries you control

Per-conversation tracing, scoring and cost accounting

Web, in-app or messaging-channel deployment

Built with

LangGraph
MCP
FastAPI
Postgres
OpenTelemetry

Tooling is chosen per engagement. This is what this kind of build typically uses, not a fixed stack we sell.

04/Example work

All work

What this looks like in practice

Reference implementations, including what went wrong.

Reference Implementation2026

Answering the calls that were going to voicemail at peak hours

A large share of calls went unanswered at peak, and most never rang back. We built a voice agent that books against the real calendar, handles the routine majority, and hands anything clinical straight to a human.

Read it

05/Also in this category