Traditional rule-based chatbots deflect 70% of conversations to agents. LLM-powered chatbots understand intent, handle edge cases and resolve the majority of queries without human escalation.
An AI chatbot handles your 3am support spike, international customers in every timezone and peak season volume without hiring. Every conversation costs the same regardless of volume.
AI chatbots with customer data access deliver personalised responses — knowing history, plan, open issues and purchase behaviour. A level of personalisation that scales infinitely.
AI support chatbots connected to your knowledge base, ticketing system and customer data — resolving tier-1 queries automatically, escalating complex cases to agents with full context, and learning from resolved tickets over time.
AI sales bots engaging website visitors, qualifying leads based on your ICP criteria, answering product questions, handling objections and booking meetings directly into sales calendars. Active 24/7.
Internal AI assistants answering employee questions about HR policies, IT procedures and operational processes — connected to your internal knowledge base. Reduce internal ticket volume by 40-60%.
In-product AI onboarding assistants guiding users through features contextually, answering questions based on where they are in the product and surfacing relevant help content proactively.
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In-product support bots, onboarding assistants and knowledge base chatbots — reducing support load and improving activation rates.
Shopping assistants, order status bots, returns automation and product recommendation chatbots.
Patient intake bots, appointment scheduling assistants and health information chatbots — with HIPAA-aware data handling.
Account query bots, transaction dispute handlers and financial product recommendation chatbots with security controls.
Property enquiry bots, lead qualification assistants and booking coordinators for platforms and agencies.
Internal HR policy bots, IT helpdesk assistants, compliance Q&A tools and employee onboarding chatbots.
See how we've helped startups and enterprises with ai chatbot development — delivering measurable outcomes.
At Fortmindz, our chatbot development process is built to produce bots that actually resolve — not bots that impress in a demo and frustrate in production. Every phase is designed around the real conversations your users will have.
Rule-based chatbots follow decision trees — if the user says X, respond with Y. They break when users phrase things unexpectedly and require constant maintenance. AI chatbots powered by LLMs understand intent in natural language, handle edge cases, access real information and improve over time.
We build for website chat (Intercom, Drift, Crisp, custom), WhatsApp Business API, Slack, Microsoft Teams, mobile apps and voice interfaces. We also build custom chat interfaces from scratch when no existing platform fits the use case.
Yes. We integrate AI chatbots with Salesforce, HubSpot, Zendesk, Freshdesk and Intercom — so the bot knows customer history, plan details, open tickets and purchase behaviour before the conversation starts. It can also create tickets, update records and log conversations automatically.
We use RAG to connect the chatbot to your knowledge base, documentation and policy documents. The bot retrieves relevant context for each question and generates accurate, cited responses. When your documentation changes, the bot updates automatically — no manual retraining.
We build escalation logic that hands off to a human agent when the bot reaches its confidence threshold — passing the full conversation history, suggested response and customer context. We also implement sentiment detection that triggers escalation when frustration is detected, before the user asks.
A focused support or sales bot connected to an existing platform (Intercom, HubSpot) takes 3-5 weeks. A custom conversational interface with multiple integrations and a custom knowledge base takes 6-10 weeks. An enterprise internal ops assistant with SSO, audit logging and complex integrations takes 8-14 weeks.
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