We build intelligent chatbots powered by GPT-4o, Claude, and Gemini — with RAG architecture for company knowledge, multi-turn memory, CRM integration, and seamless human escalation — deployed across web, WhatsApp, Telegram, and Slack.
Comprehensive solutions designed around your business goals — built by specialists who've deployed these systems at scale.
Resolve 70%+ of queries automatically with LLM-powered understanding, session memory, and contextual human handoff when needed.
Qualify inbound leads, book demos, answer product questions, and push qualified contacts directly into your CRM pipeline.
Answers questions sourced from your PDFs, Notion, Confluence, and SharePoint with cited references — no hallucinations.
Answer policy queries, guide new-hire onboarding, handle leave requests, and escalate to HR — cutting repetitive HR queries by 60%.
Product recommendations, order tracking, return processing, and personalised guidance across web chat and WhatsApp.
One AI engine deployed across your website, WhatsApp Business, Telegram, Slack, and MS Teams simultaneously.
Pure LLM chatbots hallucinate. Rule-based bots break on unexpected inputs. RAG-powered chatbots ground every response in your actual documentation — giving you the fluency of LLMs with the accuracy of structured knowledge bases.
RAG grounds every answer in indexed documentation — dramatically reducing fabricated responses vs. bare LLM chatbots.
GPT-4o and Llama 3 handle Hindi, Tamil, Bengali, Marathi, and 50+ languages — crucial for Indian market deployments.
Resolution rate, escalation frequency, CSAT scores, and unanswered question reports surface in a live dashboard.
Battle-tested LangChain and LlamaIndex stacks plus our chatbot accelerator reduce first-deployment timelines dramatically.
A structured, agile methodology that delivers on time, on budget, and beyond expectations — every single time.
Define bot scope, conversation flows, tone, escalation triggers, and channel integration requirements.
Index your documentation, FAQs, and knowledge sources into a vector database with semantic chunking.
Configure LLM, system prompts, RAG pipeline, and guardrails for accurate, on-brand responses.
Deploy across web widget, WhatsApp API, Telegram, or Slack with authentication and analytics tracking.
End-to-end conversation testing, edge case handling, and phased rollout with live monitoring dashboard.
We combine technical depth with business pragmatism — delivering solutions that create real, measurable impact.
RAG architecture grounds every response in your actual docs — your customers never receive confident but incorrect answers.
On-premise LLM hosting (Llama 3, Mistral), private API endpoints, and data residency for regulated industries.
Live dashboard showing resolution rate, escalation rate, CSAT, and top unanswered questions for continuous improvement.
First working bot in 3–4 weeks — we don't start from scratch, we build on proven LangChain + RAG stacks.
Everything you need to know before getting started.
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