Custom AI agents that think, act and execute real business tasks by Bhavy ShekhaliyaCustom AI agents that think, act and execute real business tasks by Bhavy Shekhaliya
Custom AI agents that think, act and execute real business tasksBhavy Shekhaliya
Your Business Doesn't Need Another Chatbot
You've seen the demos. A chat window that answers questions, maybe pulls from a knowledge base, maybe sounds smart. But when a real task lands in front of it — it stalls, hallucinates, or just says "I can't do that."
That's not an AI agent. That's a dressed-up FAQ bot.
Chatbots respond. Agents act.
Chatbots answer questions. Agents complete tasks.
Chatbots wait for instructions. Agents reason through problems.
Chatbots live in a widget. Agents live inside your operations.
This service builds the real thing.
I design and build custom AI agents that can:
✅ Reason through multi-step problems
✅ Make decisions based on context and rules
✅ Use tools — APIs, databases, browsers, files, code
✅ Complete tasks autonomously or pause for human approval
✅ Connect directly to your existing systems and workflows
FAQs
AI agents automate decision-driven tasks like lead qualification, support triage, reporting, and operational workflows, reducing manual effort and turnaround time.
Automation follows fixed rules, chatbots respond to queries, while AI agents can reason, choose actions, and use tools to complete end-to-end tasks.
Agent behavior is designed around your workflow, rules, and approval points, not generic prompts or assumptions.
Yes. AI agents can connect to CRMs, databases, internal tools, APIs, and communication platforms without changing your current stack.
You control autonomy levels — agents can act independently, request approvals, or operate with human-in-the-loop safeguards.
Reliability is ensured using validation rules, fallback logic, error handling, and continuous testing based on real scenarios.
Risks are managed through access control, decision limits, logging, and approval checkpoints for sensitive actions.
Timelines depend on complexity, integrations, and autonomy level, and are defined clearly after reviewing the use case.
Yes. Agents are designed to handle higher volumes, additional tools, and expanded responsibilities over time.
Yes. Data access, permissions, and storage are carefully designed to meet security and privacy requirements.
Yes. Agents are documented and built for maintainability so your team can monitor, update, and extend them.
Post-delivery support includes fixes, tuning, and adjustments based on real-world usage.
You've seen the demos. A chat window that answers questions, maybe pulls from a knowledge base, maybe sounds smart. But when a real task lands in front of it — it stalls, hallucinates, or just says "I can't do that."
That's not an AI agent. That's a dressed-up FAQ bot.
Chatbots respond. Agents act.
Chatbots answer questions. Agents complete tasks.
Chatbots wait for instructions. Agents reason through problems.
Chatbots live in a widget. Agents live inside your operations.
This service builds the real thing.
I design and build custom AI agents that can:
✅ Reason through multi-step problems
✅ Make decisions based on context and rules
✅ Use tools — APIs, databases, browsers, files, code
✅ Complete tasks autonomously or pause for human approval
✅ Connect directly to your existing systems and workflows
FAQs
AI agents automate decision-driven tasks like lead qualification, support triage, reporting, and operational workflows, reducing manual effort and turnaround time.
Automation follows fixed rules, chatbots respond to queries, while AI agents can reason, choose actions, and use tools to complete end-to-end tasks.
Agent behavior is designed around your workflow, rules, and approval points, not generic prompts or assumptions.
Yes. AI agents can connect to CRMs, databases, internal tools, APIs, and communication platforms without changing your current stack.
You control autonomy levels — agents can act independently, request approvals, or operate with human-in-the-loop safeguards.
Reliability is ensured using validation rules, fallback logic, error handling, and continuous testing based on real scenarios.
Risks are managed through access control, decision limits, logging, and approval checkpoints for sensitive actions.
Timelines depend on complexity, integrations, and autonomy level, and are defined clearly after reviewing the use case.
Yes. Agents are designed to handle higher volumes, additional tools, and expanded responsibilities over time.
Yes. Data access, permissions, and storage are carefully designed to meet security and privacy requirements.
Yes. Agents are documented and built for maintainability so your team can monitor, update, and extend them.
Post-delivery support includes fixes, tuning, and adjustments based on real-world usage.