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AI Chatbot Development

Chatbots People Actually Get an Answer From

Customers have learned to distrust chatbots, and usually for good reason. We build assistants that are grounded in your real content, honest about their limits, and quick to hand over to a human — the qualities that turn a deflection tool into something customers prefer.

200+
Projects Delivered
12+
Industries Served
10+
Years Experience
99%
Client Retention
What We Do

Our AI Chatbot Development Services

Everything required to take a chatbot from conversation design to a supported production service.

Conversation Design

We map the questions your customers genuinely ask, define the assistant's tone and boundaries, and design the escalation paths — the groundwork that determines whether the finished bot feels helpful or obstructive.

Knowledge Grounding

Your help centre, policies, product data and past tickets become a governed knowledge base the assistant answers from, so responses reflect current reality rather than a model's general impressions.

Systems Integration

Connected to your CRM, order management, ticketing and account systems, the assistant can check an order or raise a case — not merely describe how the customer might do it themselves.

Omnichannel Deployment

One assistant, consistent behaviour, deployed across your website, mobile app, WhatsApp, and messaging platforms, with conversation history following the customer between them.

Safety & Guardrails

Topic boundaries, refusal behaviour, PII redaction and profanity handling, tested adversarially before launch so the assistant behaves predictably when users push at its edges.

Analytics & Tuning

Dashboards covering resolution rate, escalation reasons and unanswered questions, with a regular tuning cycle that turns real conversations into measurable improvement.

Our Approach

Capabilities Built In

The behaviours that separate a useful assistant from an irritating one.

Context Retention

Follow-up questions work naturally. The assistant remembers what was discussed earlier in the conversation and what it already knows about the signed-in customer.

Clean Human Handover

When escalation is right, the assistant transfers to an agent with the full transcript and a summary attached, so the customer never has to repeat themselves.

Multilingual

Detects and replies in the customer's language while keeping your product terminology and brand voice consistent across all of them.

Action Taking

Authenticated users can track an order, update a detail, book an appointment or raise a ticket directly in conversation, within the permissions their account already has.

Use Cases

Where Our Chatbots Are Working

Common deployments and the operational pressure each one relieves.

Customer Support

Resolve the repetitive majority of enquiries instantly and around the clock, freeing agents for the cases that genuinely need judgement.

Employee Helpdesk

Answer HR, IT and policy questions internally, cutting the interruption load on teams that spend a surprising share of their week answering the same questions.

Sales & Lead Capture

Qualify enquiries, answer product questions, and book meetings while intent is high rather than waiting for a callback the next working day.

Retail & E-commerce

Order tracking, returns, sizing and stock questions handled conversationally, reducing both contact volume and abandoned baskets.

Healthcare

Appointment booking, pre-visit information and administrative questions, with careful boundaries around anything clinical.

Financial Services

Balance and transaction queries, product explanation and application support, inside the audit and consent requirements the sector demands.

Why Inperge

Why Our Chatbots Perform

It Says When It Doesn't Know

Grounded retrieval and explicit refusal behaviour mean the assistant escalates rather than improvises. One confidently wrong answer costs more trust than ten honest handovers.

Genuinely Integrated

Read-and-write access to your systems is what separates an assistant that resolves a problem from one that only explains the problem back to the customer.

It Improves After Launch

We treat go-live as the start. Unanswered questions and escalation patterns feed a tuning cycle that measurably raises resolution rates over the months that follow.

Technology

Our Chatbot Technology Stack

Language & AI

  • Claude
  • GPT
  • Gemini
  • Python
  • LangChain
  • Open-weight models

Channels

  • Web widget
  • iOS & Android
  • WhatsApp
  • Slack
  • Microsoft Teams
  • Voice / IVR

Integrations

  • Salesforce
  • HubSpot
  • Zendesk
  • Freshdesk
  • Shopify
  • Custom REST APIs

Platform

  • AWS
  • Azure
  • Google Cloud
  • Docker
  • Kubernetes
  • Postgres / pgvector
FAQs

AI Chatbot Development — Common Questions

A rule-based bot follows a decision tree and fails the moment a customer phrases something unexpectedly. An LLM-based assistant interprets intent from natural language and composes an answer from your knowledge base, so it handles the long tail of phrasings that a decision tree cannot enumerate. It also understands context across a conversation rather than treating each message independently.

It depends heavily on how repetitive your contact mix is and how good your existing documentation is — which is why we measure it during discovery against your real ticket history rather than quoting an industry average. Organisations with a well-maintained help centre and a high proportion of routine questions see the strongest results.

A focused assistant over a defined knowledge base can reach pilot quickly. Timelines extend with the number of system integrations, languages and channels, and with compliance review in regulated sectors. We phase delivery so a useful version is live and learning while later scope is still being built.

Yes. We integrate with the major platforms including Zendesk, Freshdesk, Salesforce and HubSpot, and with in-house systems over their APIs. Escalation creates a properly attributed ticket with the transcript attached, so it fits your existing agent workflow.

Topic boundaries and refusal rules constrain what it will discuss, retrieval grounding constrains what it can assert, and we adversarially test the assistant before launch specifically to find failure modes. High-risk categories are routed straight to a human rather than answered.

We monitor resolution and escalation, review unanswered questions, and run a regular tuning cycle covering knowledge gaps, prompt adjustments and new integrations. Support arrangements are agreed up front, whether that is us operating it or your team taking it on.

Give your customers an assistant worth using

Send us your most common enquiries and we will show you honestly how much of that volume an assistant could resolve.