AI Agents Built for Indian Business, Deployed in Weeks

A chatbot answers questions. An AI agent takes action. A chatbot replies to typed messages. An AI agent connects to your systems — WhatsApp, Zoho CRM, Razorpay, Tally, Freshdesk — reads inputs from multiple sources, makes decisions, and completes multi-step workflows without manual direction. It can check stock, update a CRM record, send a WhatsApp message, process a GST invoice, and report back — all automatically, in sequence.

AI agents are best at high-volume, rule-based work that currently eats your team's time: answering the same WhatsApp customer queries, qualifying inbound leads from Facebook or Instagram, processing GST invoices, updating Zoho CRM records after a payment, booking appointments, routing Shiprocket delivery exceptions, and generating weekly sales reports. If your team does it more than a few times a day and it follows a pattern, an AI agent can handle it.

Six core types: WhatsApp Support AI (24/7 support bots on Interakt/Wati that handle queries and escalate to humans), Sales AI (lead qualification, outreach on WhatsApp, demo booking), Operations AI (GST invoice processing, PO automation, scheduling), Data & Analytics AI (weekly reporting agents that pull from your CRM or ERP and send summaries), Voice AI (Exotel-based agents that handle inbound calls), and Document Processing AI (agents that extract data from PDFs, invoices, and KYC documents).

We use Claude (Anthropic), GPT-4o (OpenAI), Gemini (Google), and open-source models like Mistral and LLaMA depending on your workflow, cost sensitivity, and data privacy requirements. For orchestration we use LangChain, LangGraph, n8n, and Make.com. We don't have a preferred vendor — we pick the right model for each use case and explain the reasoning in plain language.

Yes — WhatsApp AI is one of our most common India deployments. We build agents on Interakt, Wati, AiSensy, and Yellow.ai that qualify leads, answer product questions, send order updates, book appointments, and escalate to human agents when needed. The AI reads your Shopify/WooCommerce, Zoho CRM, or Google Sheets in real time and responds in Hindi, English, or any regional language.

We integrate with the full Indian stack: Zoho CRM and Freshdesk for customer management, Razorpay and PayU for payment events, Tally ERP and Busy for accounting, Shiprocket and Delhivery for logistics, Interakt/Wati/AiSensy for WhatsApp, Exotel for IVR and voice, LeadSquared for sales pipelines, and Google Workspace. If your platform has an API or webhook, we can connect to it.

Yes. We build agents that extract invoice data, validate GSTINs via the GST portal API, calculate IGST/SGST/CGST automatically, flag mismatches, and push data to your accounting software — eliminating hours of monthly manual reconciliation. The agent creates an audit trail for every transaction it processes, which makes CA reviews significantly faster.

Yes. We configure agents to respond in Hindi, Hinglish, Marathi, Tamil, Telugu, Gujarati, Kannada, and other languages using multilingual LLM capabilities and automatic language detection. For WhatsApp deployments, the agent detects the language the customer writes in and responds accordingly.

Five stages: Discover (60-minute call to map workflows and size ROI), Architect (design agent logic, integrations, and guardrails — you approve before we build), Build (weekly demos throughout), Train & Test (real scenarios including Hindi queries, GST edge cases, peak volumes), and Deploy (launch with monitoring, dashboards, recorded handover in Hindi or English).

Simple single-workflow agents — a WhatsApp support bot, a lead qualifier, an invoice processor — go from kickoff to live in 2–3 weeks. Multi-workflow platforms with CRM and WhatsApp integrations take 4–6 weeks. Enterprise systems run 8–12 weeks. We give you a firm timeline after the discovery call, not before, because scope drives everything.

Weekly demos throughout — no exceptions. After every stage we show you what's been built and how it behaves. You can give feedback, adjust the logic, and reprioritise features before we move on. Most clients find that seeing the agent working early changes their thinking about what's possible, and we build room for that.

Every engagement includes a 30-day post-launch support window. During that period we fix bugs, tune the agent's behavior based on real usage, and run a training session for your team. After 30 days, you can continue on a monthly retainer or manage it yourself — the dashboard is built for non-technical operators and all code and API keys are yours.

FactoryJet AI agents start from ₹4,00,000 for a focused single-workflow agent. Most Indian businesses need the Growth tier from ₹12,00,000, covering multiple interconnected agents, CRM/WhatsApp integrations, and a management dashboard. Enterprise multi-agent platforms start from ₹20,00,000. All prices are fixed — no hourly billing surprises.

The most common return is labor hours recovered. A WhatsApp support agent handling 70% of queries replaces the equivalent of 2–3 support executives at a fraction of the monthly cost. A lead qualification agent that responds to every inbound WhatsApp message within 60 seconds typically increases conversion rates by 20–35%. Most clients see payback within 3–6 months of launch.

Two types: LLM API costs (typically ₹5,000–₹25,000/month for most Indian SMB volumes — these go directly to model providers, we don't mark them up) and optionally a FactoryJet retainer for ongoing optimisation or new features. The retainer is optional; many clients self-manage after the handoff.

No. We build every agent with a non-technical operator in mind. The management dashboard lets you see what the agent is doing, review flagged items, adjust thresholds, and pause or resume workflows — without touching code. We include a recorded training walkthrough in Hindi or English specific to your agent.

Yes — most of what we build is custom. We've built agents for jewellery GST compliance, EdTech enrolment funnels, pharmaceutical distribution reorders, NBFC loan application intake, and hospital patient scheduling. The underlying architecture is the same; the workflow logic, prompts, and data connections are built specifically for your process.

We architect agents with modular integration layers — the agent logic is separated from the connector code. Switching from Freshdesk to Zoho Desk, or from Razorpay to PayU, typically means updating the integration module, not rebuilding the agent from scratch. Days of work, not months.

Yes. We use API-level integrations (no screen scraping), enforce least-privilege data access so the agent only reads what it needs, and implement full audit trails on every action. For regulated sectors — BFSI, healthcare, legal — we can deploy private LLM setups that process your data without sending it to third-party model providers.

Every agent includes confidence thresholds (if the model isn't sure, it escalates to a human rather than guessing), guardrails on high-stakes actions (the agent asks for approval before processing payments, sending bulk WhatsApp messages, or updating critical records), and a full action log for auditing. No AI system is 100% accurate — responsible design means errors are surfaced and correctable, not silent.

Yes. We've built AI agents for D2C brands that reduced WhatsApp support volume by 70%, for real estate builders that doubled site visit bookings without adding telecallers, and for B2B manufacturers that eliminated 30+ hours per week of manual invoice processing. We're happy to share relevant examples during a strategy call.

Three differences: structure (flat team — you brief an engineer, that engineer builds it, no account manager layers), SMB depth (500+ small business projects since 1999, we understand what a 15-person business actually looks like operationally), and transparency (fixed-price contracts, weekly demos, and you own everything at the end — no lock-in).