Tech stack and integrations
Claude APIGoogle Geminin8nPostgreSQLElevenLabsKie.ai
Pricing approach
Project-based and scope-dependent. Book a call to discuss the workflow, complexity, integrations, and rollout plan.
Automation service
AI Agent Development - Business Automation Agents
Abhijeet builds AI agents that operate inside business workflows instead of living as isolated chatbots. The documented systems use Claude and Gemini for personalized replies, multilingual lead qualification, storyboard generation, and compliant retry loops.
What I build
Structured AI prompts with JSON-safe outputs
Lead memory and conversation context retrieval
Reply agents for LinkedIn and WhatsApp
AI storyboard and content generation pipelines
Validation and retry paths for policy or format failures
Related resources
Explore the connected automation cluster
These service, guide, and proof pages support this implementation path.
Complementary services
Service
Explore WhatsApp Automation
WhatsApp bots for lead qualification, multilingual conversations, sales alerts, and CRM handoff.
Service
Explore n8n Workflow Development
Custom n8n workflows for lead capture, CRM sync, AI enrichment, approvals, notifications, and operational automation.
Service
Explore Zoho CRM Consulting
Zoho CRM setup, custom modules, client scripts, Deluge functions, workflow rules, and cross-module automation.
Related guides
Guide
Read: How Startup Teams Can Use AI Agents to Reduce Manual Follow-Ups
Learn how startup teams can use AI agents to reduce missed follow-ups, keep CRM records updated, and improve lead response without losing human control.
Guide
Read: How to Think About Business Automation Before Building Workflows
Good automation starts with the business process, not the tool. Here is a practical way to map workflows before building in n8n, Zoho, or AI agents.
Guide
Read: n8n vs Zapier for Startups: Which Automation Platform Should You Choose in 2026?
A practical founder-focused comparison of n8n and Zapier, covering ease of use, flexibility, costs, AI workflows, and which platform startups should choose in 2026.
Related builds
Case study
See case study: Automated LinkedIn Outreach with AI Reply Agent
A full LinkedIn outreach system with scraping, gradual connection ramp-up, post engagement, acceptance tracking, campaign messaging, and Claude-powered replies with lead memory.
Case study
See case study: Multilingual WhatsApp Sales Bot for an International Freight Forwarder
A WhatsApp AI sales assistant that qualifies freight leads in English, Hindi, and Telugu, stores lead memory, and alerts sales when a quote is requested.
Case study
See case study: End-to-End AI Video Production Pipeline
A two-workflow pipeline that converts a written script into a narrated, subtitled, edited 1080p video using AI storyboarding, image generation, voiceover, and FFmpeg.
FAQ
What makes an AI agent production-ready?
A production agent needs memory, clear system instructions, structured output, validation, error handling, and a downstream workflow that can trust its data.
Can AI agents connect to CRM data?
Yes. Agents can retrieve lead profiles, past messages, and CRM context before generating replies or actions.
Can AI agents work in n8n?
Yes. The source projects use AI models inside n8n workflows for sales replies, WhatsApp qualification, storyboarding, and prompt correction.
Can an AI agent handle multiple languages?
Yes, when the prompt, memory, and message gateway are designed for language switching.
Can AI output trigger real actions?
Yes, but it should be validated and structured before it updates databases, sends messages, or creates CRM records.