vishal maurya

AI Automation Development

I automate repetitive business workflows with LLMs, APIs, background jobs and custom business logic, then deploy them so they run reliably.

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What I automate

  • Extracting and validating data from documents and emails
  • Classifying and routing requests or tickets
  • Generating drafts and summaries for human review
  • Syncing data between your systems through their APIs
  • Scheduled and event-driven jobs with retries

How it is built

Workflows run as background jobs with queues, retries and idempotent steps, so a failed run can be repeated safely. LLM calls are validated, logged and cost-limited. Everything is deployed with monitoring.

For autonomous, tool-using workflows see AI agent development. For document-heavy work see RAG development. The full range is under AI app development.

Pricing depends on scope. Tell me about your workflow.

Common questions

Which workflows are good candidates for AI automation? Repetitive, text-heavy work such as document processing, data extraction, classification, routing, report drafting and data entry between systems.

How much does AI automation cost? It depends on the number of steps, integrations, data volume, need for human review, and model usage costs. I quote after reviewing the workflow.

What happens when the AI gets something wrong? I add validation, confidence checks and a human review step for uncertain or high-impact results, and keep logs so errors can be traced.

Do you use no-code tools or custom code? Custom Python code by default, which gives control over reliability, cost and security. I can integrate with tools you already use.

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