ai-powered automation
Agents and workflows that take repetitive work off your team.
I build AI automations that handle the repetitive, judgement-light work your team does by hand — reading documents, routing requests, extracting data, drafting responses, moving information between systems. Built on AI agents and MCP tool integrations, with humans kept in the loop wherever the stakes justify it.
Sound familiar?
If any of these describe where you are right now, this is the right page.
Your team spends hours a day copying data between systems that should talk to each other.
Documents, invoices or forms arrive as PDFs and someone types them into software by hand.
Incoming requests need reading and routing before anyone can act on them.
You've tried a no-code automation tool and hit its ceiling the moment real judgement was needed.
What you get
Concrete outputs, not a vague statement of work.
- An automation workflow that runs on a schedule, a webhook, or on demand
- AI agents with real tool access — your APIs, databases, files and third-party services
- Document and data extraction pipelines (PDFs, invoices, forms, emails)
- Human-in-the-loop approval steps wherever a mistake would be costly
- Slack, email or dashboard notifications so your team sees what ran and what needs attention
- Logging and observability so every run is auditable
- Runbook documentation covering what to do when something looks wrong
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How this project would run
Five stages, so you always know where things stand and what happens next.
Discover
We find the tasks worth automating — high volume, well-defined, and currently eating real hours.
Design
I map the workflow, decide where AI genuinely helps versus where plain code is more reliable, and define the human checkpoints.
Build
Built and tested against your real data, with accuracy measured before anything goes near production.
Ship
Rolled out alongside the manual process first, so you can compare outputs before trusting it fully.
Support
Monitoring and tuning as edge cases surface — automations always meet inputs nobody predicted.
Related work
Projects where I've done exactly this kind of build.
Rubricate
rubricate.net
An agentic AI voice-interview and evaluation platform — the entire platform, built solo — that vets domain experts at scale with adaptive voice interviews backed by a full automated evaluation pipeline. The expert network behind Dataclap.
- ▹Agentic AI voice interviews that adapt to each candidate in real time
- ▹End-to-end automated evaluation pipeline with scoring rubrics
- ▹Automation workflows for sourcing, screening, and expert onboarding
KubeTrace
kubetrace.net
An AI-driven Kubernetes testing, security, and reliability platform — the entire platform, built solo. It continuously validates clusters for security, reliability, and configuration drift — and pinpoints root cause in seconds.
- ▹MCP-based multi-tool integration with real-time, read-only cluster connect
- ▹AI root-cause investigation across multi-cluster, regulated production environments
- ▹Automated security, network, performance, storage & API test suites with compliance reports
Agentic RAG Chatbot
A local agent-driven RAG system that combines LLM capabilities with tool integrations to deliver accurate, contextual AI responses without relying on external APIs.
- ▹5-step reasoning pipeline for transparent, auditable reasoning
- ▹Local AI system with tool integrations for contextual responses
- ▹No dependency on external APIs
AI-Powered Automation — questions
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Need ai-powered automation?
Book a 15-minute call and tell me what you're trying to build. You'll get a straight answer on whether I can help, what it would take, and roughly what it would cost.