AI Agents That Run Your Business While You Sleep

A chatbot answers questions. An AI agent takes action. A chatbot sits in a window and responds to what you type. An AI agent — built on the same large language model technology — connects to your tools, reads inputs from multiple sources, makes decisions, and completes multi-step tasks without you directing every move. It can check your inventory, update a CRM record, send a follow-up email, process a document, and report back on what it did — all in sequence, automatically.

AI agents are best at high-volume, rule-based work that currently eats your team's time: answering the same customer questions repeatedly, routing and triaging support tickets, qualifying inbound leads, processing invoices and documents, updating records across systems, scheduling appointments, sending follow-up sequences, and generating reports from raw data. If your team does something more than a few times a day and it follows a pattern, an AI agent can probably handle it.

FactoryJet builds six core types: Customer Service AI (24/7 support bots that handle tickets, answer questions, and escalate to humans), Sales AI (lead qualification, outreach sequencing, follow-up automation), Operations AI (invoice processing, scheduling, internal workflow automation), Data & Analytics AI (reporting agents that pull, clean, and summarize business data on demand), Voice AI (phone-based agents that handle inbound calls and book appointments), and Document Processing AI (agents that read, classify, extract, and route contracts, forms, and PDFs).

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. We don't have a preferred vendor — we pick the right model for each use case. For orchestration we use LangChain, LangGraph, CrewAI, n8n, and Make.com. Most clients don't need to think about this; we handle model selection and explain the reasoning.

We follow five stages: Discover (we map your workflows, data sources, and goals), Architect (we design the agent logic, integrations, and guardrails), Build (we develop and connect everything), Train & Test (we run the agent through real scenarios and tune its behavior), and Deploy (we launch, hand off, and train your team). Every stage ends with a demo so you see progress weekly and can course-correct before we build further.

Simple single-workflow agents — a lead qualifier, a support bot, an invoice processor — typically go from kickoff to launch in 2–3 weeks. Multi-workflow platforms with CRM integrations and dashboards take 4–6 weeks. Enterprise systems involving multiple agents, complex data pipelines, and compliance requirements run 8–12 weeks. We give you a firm timeline after the discovery session, 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 reprioritize features before we move to the next stage. Most clients find that seeing the agent working early changes their thinking about what's possible, and we build in 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 with your team. After 30 days, you can continue on a monthly retainer for ongoing optimization, or manage it yourself — the dashboard is built for non-technical operators and all code and API keys are yours.

FactoryJet's AI agents start at $5,000 for a focused single-workflow agent (Starter tier). Most small businesses need the Growth tier at $15,000, which covers multiple interconnected agents, CRM integrations, a management dashboard, and a 30-day support window. Enterprise platforms with multi-agent orchestration start at $25,000. All prices are 60–70% lower than comparable US AI agencies.

Our engineering team is based in India. That's it — no complicated explanation. The same quality of architecture, code, and delivery at dramatically lower labor costs. We don't have layers of account management, project managers, and sales reps inflating your invoice. You brief an engineer; that engineer builds it. That structure lets us pass the savings directly to you.

The most common return comes from labor hours recovered. A customer support agent handling 70% of tickets at $15,000 replaces hundreds of hours of manual work per month. A lead qualification agent that responds to every inbound lead within 60 seconds typically increases conversion rates by 20–35% — response speed is the single biggest driver of lead close rates. Most clients see payback within 3–6 months of launch.

Yes, two types: API usage costs (the AI model fees, typically $50–$300/month for most SMB use cases depending on volume — these go directly to model providers, we don't mark them up) and optionally a FactoryJet retainer if you want ongoing optimization or new feature development. The retainer is optional; many clients self-manage after the handoff.

We integrate with most business software via API: CRMs (Salesforce, HubSpot, Pipedrive, Zoho), e-commerce (Shopify, WooCommerce, Magento, BigCommerce), communication tools (Slack, Gmail, Outlook, Twilio for SMS and voice), project management (Notion, Airtable, Asana, Monday.com), databases (PostgreSQL, MySQL, Supabase, Firebase), and document storage (Google Drive, Dropbox, Box). If your platform has a REST API or webhook support, we can connect to it.

No. We design 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 — all without touching code. We also include a recorded training walkthrough specific to your agent. If something breaks or needs updating because a connected platform changed its API, you contact us and we fix it.

Yes — most of what we build is custom. We've built agents for insurance claim intake, legal document review, HVAC dispatching, wholesale reorder management, clinical scheduling, and SaaS onboarding sequences, among many others. The underlying architecture is the same; the workflow logic, prompts, data connections, and guardrails are built specifically for your process. We start with a discovery session to map the workflow before writing a line of code.

We architect agents with modular integration layers, meaning the agent logic is separated from the connector code. Swapping one CRM for another typically means updating the integration module, not rebuilding the agent from scratch — days of work, not months. We document all integration points during delivery specifically so that future changes are straightforward.

Yes. We architect with data privacy as a baseline requirement, not an afterthought. We use API-level integrations (not screen scraping), enforce least-privilege data access so the agent only touches what it needs, and implement full audit trails on every action. For regulated industries — healthcare, legal, finance — we can deploy private LLM setups that process your data without sending it to third-party model providers. All data flows are documented during delivery.

Every agent we build includes confidence thresholds (if the model isn't sure, it escalates to a human rather than guessing), guardrails on high-stakes actions (the agent requests human approval before sending emails, processing payments, or updating records it shouldn't touch autonomously), and a full action log so you can audit exactly what the agent did and when. No AI system is 100% accurate — responsible design means errors are surfaced and correctable, not silent.

It shouldn't, and we'd advise against framing it that way. AI agents work best as the first line of support — handling 60–80% of routine tickets, order status questions, and common queries automatically, around the clock, without wait times. They escalate anything nuanced, emotionally sensitive, or outside their confidence threshold to your human team. Most clients don't reduce headcount; they redirect their team to higher-value customer relationships instead of repetitive queries.

Three differences that matter: price (60–70% cheaper because our engineers are India-based, serving US businesses for 25+ years), speed (no layers of account management between your brief and the engineer building it), and SMB depth (500+ small business projects since 1999 — we understand the operational reality of businesses your size, not just enterprise AI theory). We also won't pitch you an AI agent when a simpler automation would do the job.

Yes. We've built AI agents for e-commerce brands that reduced support ticket volume by 70%, for service businesses that cut lead response time from hours to under 60 seconds, and for operations teams that eliminated 30+ hours per week of manual data entry. We're happy to share relevant case studies during a strategy call — and if we haven't worked in your specific industry, we'll tell you that upfront rather than pretend otherwise.