Services · AI Chatbot Development
Our AI chatbot development services go beyond scripted responses and basic automation. We build LLM-powered conversational AI systems that understand context, answer from your data, complete real tasks, and know when to hand off to a human all with compliance guardrails built in from Day 1.
Trusted to build
Capabilities
Chatbots that answer exclusively from your data product documentation, company policies, regulatory guidelines, course materials. Every response is grounded in verified content with source citations. No hallucinations. No fabricated answers.
Our chatbots don't just answer they complete tasks. Process insurance claims. Generate medical documentation. Collect structured data through multi-turn conversations. Trigger workflows and update systems automatically.
AI systems that listen to real-time conversations and generate structured documentation automatically clinical notes, meeting summaries, consultation records. Multi-language support with code-switching awareness.
One AI engine, multiple channels. We deploy chatbots across web chat widgets, mobile apps, WhatsApp, and voice. The conversation engine is shared only the interface adapter changes.
Chatbots that operate within strict regulatory boundaries. FCA-compliant communication records for insurance. HIPAA-compliant clinical documentation for healthcare. FERPA-compliant data handling for education. Compliance is architected from the foundation not patched after launch.
Every chatbot ships with conversation analytics query classification, resolution rates, escalation patterns, satisfaction signals, accuracy tracking. These insights drive monthly improvement cycles that measurably move accuracy.
Delivery process
Before writing code, we design the conversation architecture domain boundaries, the top 20 user intents, escalation triggers, personality and tone, accuracy requirements based on the cost of errors. ClaimBot's design specified 14 claim types with different questioning flows, escalation triggers for complex claims, and FCA-compliant language requirements for every response.
We build the retrieval pipeline that grounds your chatbot in real data. Document ingestion handles PDFs, Word documents, web pages, and video transcripts. Chunking preserves contextual boundaries. Hybrid search combines vector retrieval with keyword matching for maximum accuracy. EduAssist AI's pipeline ingests 10,000+ course documents with per-course isolated collections preventing cross-course contamination.
We select the right LLM and build the conversation engine with persistent memory, context management, and structured output parsing. Claude Sonnet for compliance-sensitive applications (ClaimBot superior instruction-following, low hallucination on structured extraction). GPT-4o for complex reasoning and natural conversation (ScribeAI clinical NLP processing). Gemini for multimodal chatbots that process images and documents alongside text.
We deploy across web chat, mobile, WhatsApp, and voice with the same AI engine powering every channel. Voice channels use Whisper for speech-to-text and ElevenLabs for natural voice responses. ClaimBot operates on web chat and phone using the same LangChain agent with voice-specific adaptations.
AI chatbot testing goes beyond functional testing. We test accuracy, hallucination resistance, prompt-injection resistance, edge case handling, and escalation reliability. EduAssist AI's testing included prompt injection attempts by students trying to bypass academic integrity modes the two-stage intent classifier catches these before they reach the generation layer.
Tech Stack
| Large language models | Claude Sonnet (compliance-sensitive), GPT-4o (complex reasoning), Gemini (multimodal) |
| RAG and retrieval | LangChain, Qdrant / Pinecone, BM25 + hybrid search |
| Voice and multi-channel | Whisper Large-v3 (speech-to-text), ElevenLabs / Azure Speech (text-to-speech), Twilio (telephony), Meta Business API (WhatsApp) |
| Frontend & backend | React (chat widgets), Node.js / Python FastAPI (backend), AWS / GCP (serverless) |
Why TechEniac
Most AI chatbots pull answers from general knowledge. Ours pull answers exclusively from your verified knowledge base. We build RAG pipelines that ingest your documentation PDFs, help articles, web pages, video transcripts and ensure every response is grounded in content you control.
A chatbot that forgets what was said two messages ago is frustrating. We implement per-user conversation memory with persistent context storage the chatbot remembers previous interactions within a session and, where appropriate, across sessions.
The most important thing an AI chatbot can do is know when to stop. We design explicit escalation triggers confidence thresholds, topic boundaries, complexity indicators that route conversations to human agents at exactly the right moment.
Book a free 30-minute strategy session. We’ll review your product idea, discuss architecture options, and map a realistic path from idea to launch.