AI CHATBOT DEVELOPMENT

An AI that knows your business inside out

Custom LLM-powered bots trained on your documentation and data. 78% ticket deflection, sub-500ms responses, multi-channel deployment — built for production, not demos.

How we build it

Ticket deflection rate (TBD)

Response time (TBD)

User CSAT score (TBD)

Languages supported (TBD)

Aria — Support AI

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What is our refund policy for premium plans?

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Premium plans have a 30-day money-back guarantee. To initiate a refund, go to Settings → Billing → Request Refund. Refunds process within 5–7 business days.

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Can I get a prorated refund after 45 days?

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After 30 days, partial refunds are evaluated case-by-case. Please share your account email and I can escalate to our billing team right now.

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Web WidgetWhatsAppSlackTelegramREST API

Models & frameworks we use

· GPT-4o· Claude 3.5 Sonnet· Gemini 1.5 Pro· Llama 3· Mistral· LangChain· LlamaIndex· Pinecone· Weaviate· OpenAI Embeddings· Whisper (voice)· ElevenLabs

Capabilities

Beyond FAQ bots — AI that acts

RAG Knowledge Base

Retrieval-Augmented Generation on your own documentation, FAQs, product data, and policies. The bot answers from your knowledge, not hallucinations.

Multi-Channel Deployment

One bot, everywhere: web widget, WhatsApp Business API, Slack, Microsoft Teams, Telegram, and REST API for custom integrations.

Custom Fine-Tuning

Fine-tune foundation models on your domain-specific data for dramatically better accuracy on industry-specific terminology and workflows.

Function Calling & Actions

Bots that don't just answer — they act. Book appointments, check order status, process refunds, update CRM records, and trigger workflows.

Multilingual Support

Native Hindi, Tamil, Telugu, Bengali, and 50+ language support for pan-India customer bases. Language auto-detection, seamless switching.

Enterprise Security

No training data sent to model providers. On-premise deployment option. PII redaction, data residency controls, and audit logging.

Build process

From knowledge base to production bot

Use Case Definition

Define the 5–10 core intents the bot must handle. Success metrics defined (CSAT, deflection rate, resolution rate). Scope scoped to what matters most.

Knowledge Architecture

Audit existing documentation, FAQs, and data sources. Structure knowledge base for optimal RAG retrieval. Gap analysis — what content needs to be created.

Build & Evaluate

Develop RAG pipeline, configure model parameters, implement guardrails. Evaluate on 200+ test cases covering edge cases, adversarial inputs, and tone.

Integrate & Deploy

Connect to your channels (web, WhatsApp, Slack). CRM/helpdesk integration (Freshdesk, Zendesk). Human handoff workflow configured.

Monitor & Improve

Post-launch analytics: deflection rate, CSAT score, unanswered question log. Monthly model updates and knowledge base refreshes included for 3 months.

Deliverables

Production-ready bot with 3-month support

Trained and deployed AI chatbot (all specified channels)
Knowledge base with RAG pipeline (source + vector store)
Admin dashboard for bot management and analytics
Conversation logs and performance analytics
Human handoff integration with your helpdesk
API documentation for custom integrations
3-month post-launch monitoring and model updates
Staff training session on bot management

Your data stays yours

No training data shared with model providers. On-prem deployment available for max data privacy.

78% deflection rate

Average ticket deflection measured across our chatbot deployments — industry average is 40%.

Continuous improvement

Monthly knowledge base updates and model evaluations for 3 months post-launch.

Human handoff built-in

Graceful escalation to human agents with full conversation context passed automatically.

Common questions

AI chatbot questions, answered

We work with all major foundation models and recommend based on your use case. GPT-4o is best for general customer support. Claude is excellent for long-context document analysis. Gemini 1.5 Pro handles multimodal inputs (images, PDFs). For cost-sensitive high-volume use cases, we fine-tune open models like Llama 3.

No. We use API access to foundation models, not training pipelines. Your conversation data is never used to train OpenAI, Anthropic, or Google models. For maximum data privacy, we offer on-premise deployment using open-source models (Llama 3, Mistral) running on your infrastructure.

We implement a graceful escalation workflow: the bot detects low-confidence responses, acknowledges uncertainty honestly, and routes to a human agent with full conversation context. We monitor "unanswered question" logs weekly to expand the knowledge base and eliminate gaps.

Yes. We have pre-built integrations with Freshdesk, Zendesk, Salesforce Service Cloud, Zoho Desk, and HubSpot. Custom REST API integrations are available for proprietary systems. The bot can read from and write to your CRM in real-time during conversations.

We track: ticket deflection rate (% of queries resolved without human), first response time, CSAT scores, average handle time reduction, and support cost per ticket. Most clients see 60–80% ticket deflection within 60 days, translating to 30–50% reduction in support team workload.

Proof of concept in 1 week

See your AI bot answer real questions

We'll build a working proof-of-concept using your actual documentation within one week — before you commit to a full engagement.