Custom AI Workflows
Document understanding, autonomous loops, extraction, intelligence.
The bespoke bucket. Document pipelines that turn PDFs and images into structured data. Cron-driven autonomous loops. Scraping agents and lead-intelligence systems.
What you get
4 pillarsDocument → structured data
OCR + LLM pipelines for invoices, contracts, IDs, lab reports — anything you need turned into rows.
Autonomous loops + alerts
Cron-driven agents that watch a data source, summarise overnight, and alert when a threshold trips.
Lead + market intelligence
Targeted scraping + enrichment agents that surface deal-worthy leads, not generic firehose data.
Bespoke designs
If the workflow doesn’t fit a named bucket, we design it from the goal backwards.
Tools we reach for
Not exhaustiveMore in AI Systems Building
Core overview →Personal AI Assistance
A principal-grade assistant across every channel you use.
Business Operations Manager
A multi-agent team that runs a business function 24/7.
AI Software Developer
Agent harnesses that write, review, and ship code.
RAG + Knowledge Systems
Retrieval-augmented chat over a real corpus, with citations.
Messaging Agents
WhatsApp, Telegram, Discord, Slack, iMessage, and web-chat bots.
Agent Orchestration Platform
A fleet of specialised agents, one bridge across your messaging apps.
Real-Time Voice Agents
Live phone and browser-voice agents with streaming and barge-in.
AI Evals + Observability
Test, trace, and keep agents honest in production.
Frequently asked
4 questionsWhat kinds of custom AI workflows do you build?
Document understanding (contracts, invoices, resumes), data extraction at scale, web research and scraping, lead intelligence, autonomous loops for repetitive ops, and any "if a human had to spend hours on this, automate it" task.
How does web scraping handle bot detection and legality?
Headless Playwright with stealth profiles, rotating proxies, and rate limiting. We only scrape public data, respect robots.txt where applicable, and avoid sites with explicit anti-scraping ToS. Compliance review happens before code.
Can it run long jobs — hours or days?
Yes — durable workflow runners (BullMQ, Inngest, Vercel Workflow DevKit) handle crash recovery, retries, and resume-from-step. Jobs that take days survive deploys, restarts, and provider outages.
How does it connect to my internal systems?
Direct API integrations, MCP servers for tool exposure, database connections, or a thin adapter layer when an API does not exist. Auth via OAuth, service accounts, or signed webhooks depending on the system.
Sounds like the bucket you’re in?
Tell me what you’re trying to build. I’ll send a written proposal within 48 hours of our discovery call.