// CATEGORY
All Custom Software
Purpose-built software, engineered for the pace of live events and modern business.
ExploreLLM-powered chatbots and support automation that resolve attendee and customer queries instantly across web, WhatsApp, and in-app channels.

Every event and product generates the same flood of repetitive questions—where do I register, what time is the keynote, how do I get a refund? ZebIQ builds AI assistants on modern large language models, grounded in your own content through retrieval-augmented generation (RAG), so answers are accurate, on-brand, and current—not hallucinated. Deploy across web, WhatsApp, apps, and internal tools. Support that scales.
Your support team spends 60–80% of their time answering the same questions. AI chatbots eliminate that bottleneck:
But generic chatbots hallucinate. Ours don't, because every answer comes from your approved content.

Retrieval-Augmented Generation (RAG) grounds every response in your verified content—event guides, policies, product docs, schedules—dramatically reducing hallucination risk. The assistant retrieves relevant chunks, synthesizes answers, and declines gracefully when it's out of scope. No made-up flight times, refund policies, or session details.
We treat conversational AI as an engineering discipline, not magic. Guardrails, prompt-injection protection, conversation analytics, and a feedback loop that retrains the knowledge base from unresolved queries mean your assistant gets measurably better every week it runs.
One assistant, deployed across your website, event app, WhatsApp Business API, Slack, Teams, and internal tools. Customers reach you where they already are.
The bot queries your registration, ticketing, or order systems via secure API to answer personal questions—booking status, schedule conflicts, order history—in real time.
Complex queries route to your support team with full transcript and detected intent. Customers never repeat themselves; your agents work faster.
Serve attendees in English, Hindi, and major regional languages from a single knowledge base. Personas and tone adapt per language.
Dashboards for resolution rate, top intents, failure points, and user satisfaction. Scheduled knowledge-base refreshes keep accuracy high as your content changes.
Prompt-injection protection, conversation audit logs, PII redaction, and role-based access control for integrations. Your data is never used for model training unless you opt in.
We collect and structure your FAQs, policies, schedules, documentation, and product specs into a clean, versioned knowledge base. No messy spreadsheets—structured, searchable, and ready for RAG.
We define persona, tone, guardrails, escalation rules, and system integrations the bot needs to answer real queries—ticketing lookups, refund workflows, schedule searches, etc.
We implement the RAG pipeline and run edge cases, off-topic prompts, injection attempts, and boundary tests. You approve the assistant before any customer sees it.
A controlled pilot with live traffic validates resolution rates and user experience. Then full deployment across your channels—web, app, WhatsApp, Slack—with rollback safety.
Weekly analytics reviews, knowledge updates, and feedback loops keep accuracy high as your content, events, and audience evolve. We tune, you focus on growth.

Conversational AI is not a novelty—it's the new standard for customer and employee experience. The barrier is not the technology anymore; it's getting the architecture right: grounded, safe, connected to your systems, and continuously learning. That's the difference between a demo and a product.
We engineer specifically against this. Answers are grounded in your approved content via RAG, the assistant is instructed to decline rather than guess, and every deployment goes through adversarial testing before launch. Out-of-scope queries route to a human. You control the knowledge base; the bot can't invent answers.
We are model-agnostic and select based on your accuracy, latency, cost, and data-residency requirements—including options where your data is never used for model training. The architecture lets us swap models as the landscape evolves, so you're not locked in.
Yes. We build secure API connectors so the assistant can read live data (bookings, ticket status, schedules, inventory) and write back (create tickets, update records) with proper authentication, audit logging, and role-based access control.
Typically 4–8 weeks from kick-off to go-live, depending on knowledge-base complexity and system integrations. A simple FAQ chatbot can be live in 2–3 weeks; a multi-channel assistant with live CRM lookups and escalation workflows takes longer—but the payoff is immediate.
The knowledge base is versioned and easy to update. We can set up automated refreshes from your source docs (event schedule feeds, product catalogs, help article repos) or manual uploads. Your assistant stays current without engineer involvement.
Let's talk about your support challenges, your channels, and your knowledge base. We'll sketch a design, estimate timelines, and show you the payoff.
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