Services
AI & Automation
Pipelines that run without you
I build multi-agent systems, content automation pipelines, OCR workflows, and AI integrations. These are production systems handling real throughput, not proof-of-concept notebooks. I've shipped and maintained them myself.
What I build
Multi-Agent Pipelines
I architect systems where agents hand off tasks to each other (research, writing, review, publishing) without human checkpoints in the loop. Built on Claude's agent SDK with real orchestration.
- MGT Mission Control: agent orchestration backend
- 10+ specialized agents deployed to production
- Parallel execution with dependency-aware scheduling
Content Automation
End-to-end content pipelines. From raw footage or source data to formatted, published output. I've built systems that handle video processing, transcript generation, clip extraction, and distribution.
- MGT Factory: content automation microservice
- Automated clip detection and export
- Multi-platform publish workflows
OCR & Document Processing
Extract structured data from PDFs, images, and scanned documents. I've built OCR pipelines for real estate and legal documents that feed directly into databases and downstream systems.
- Title document extraction for real estate workflows
- Structured data output to Postgres
- Error correction and confidence scoring
AI Integrations
Connecting existing apps to AI capabilities: chat interfaces, classification, summarization, generation. I wire Claude, OpenAI, and open-source models into production systems that handle real request volumes.
- Claude-backed Discord moderation
- AI-assisted CRM data enrichment
- Streaming inference endpoints for web UIs
How it works
01
Workflow Mapping
I map your current manual process step by step. Where does data come from? What transforms happen? What's the output? I need to understand what's manual before I can automate it.
02
Architecture Design
I design the pipeline architecture: which steps get AI, which get deterministic logic, where humans stay in the loop. You get a system diagram and cost projection before any code is written.
03
Pipeline Build
I build and test against your real data, not sample inputs. Each pipeline stage gets error handling, retry logic, and observability. You see outputs from day one.
04
Deploy & Optimize
Production deployment with monitoring dashboards, alerting, and cost tracking. I optimize prompt costs and latency over the first 30 days based on real usage patterns.
Who this is for
Ops-heavy businesses
You have staff manually processing documents, categorizing data, or copying information between systems. The work is repetitive and the rules are clear enough for automation.
Content teams
You produce content at scale (video, written, social) and need pipelines that handle processing, formatting, and distribution without a 10-person team.
Technical founders
You know AI can help your product but need someone who has shipped real AI systems to architect and build it. Not a prompt engineer. A systems engineer.
What clients say
“David built our entire Discord marketplace from scratch: ticket system, escrow, AI moderation, the whole thing. We went from 0 to 2,000 members and $10K revenue in three months. The bots run 24/7 without issues.”
Live systems
MGT Studio
Unified platform with /control, /factory, and /ops modules. 26+ routes, 20+ deployed agents.
MGT Factory
Content automation backend as a microservice. Handles clip processing and distribution pipelines.
MGT Mission Control
Agent orchestration backend with real-time task delegation and status tracking.
Claude Agents (Open Source)
Public repo of production-ready agent implementations. github.com/davidolverson/claude-agents
Stack I use
Claude API (claude-sonnet-4-6)OpenAI APIPython (pipelines)TypeScript (integrations)LangGraph / custom orchestrationPostgres + vector searchFFmpeg (media)Railway / Fly.io
Pricing
AI automation projects range from $499 to $2,499 depending on pipeline complexity. Single-workflow automations with one AI stage start around $499. Multi-agent orchestration systems with monitoring, multiple data sources, and production observability run $1,499 to $2,499. I scope everything after understanding your actual data flow. No guessing.
Related case studies
Frequently asked questions
What business processes can be automated with AI?
Document processing, content generation, data classification, customer support triage, lead enrichment, report generation, and any repetitive workflow with clear rules. If your team copies data between systems or follows the same steps repeatedly, it can likely be automated.
How much does AI automation cost for a small business?
Single-workflow automations with one AI stage start around $499. Multi-agent orchestration systems with monitoring and multiple data sources run $1,499 to $2,499. I scope everything after understanding your actual data flow, so you get an exact number before any code is written.
Do you integrate with existing tools?
Yes. I've integrated with Postgres, Supabase, Notion, Google Sheets, Slack, Discord, S3, and dozens of REST APIs. If it has an API, I can connect it.
How long does an AI automation project take?
Simple single-stage automations: 1-2 weeks. Multi-agent pipelines with custom orchestration and monitoring: 4-8 weeks. I build against your real data from day one, so you see working outputs early.
What if the AI makes mistakes?
Every pipeline includes confidence scoring and human-review checkpoints for edge cases. I design for graceful failure. Bad outputs get flagged, not shipped. The system improves over time as I tune prompts against real failure cases.
Stop doing it manually.
Describe the workflow. I'll map out an automated version and tell you whether AI is the right tool for it.
// BEFORE THE QUOTE
Agent pipelines, in production. Not a demo.
The exact model + tool stack behind MGT Studio, Factory, and Mission Control. Shipped agents, teardowns, and measurable outcomes.
Stack Explorer
Claude, OpenAI, local models, MCP, TurboPuffer, queues, OCR, and every orchestration layer.
Open the stack→
Ship Log
Every AI platform shipped (MGT Studio, Factory, Mission Control, X Engine, and more).
Scan the log→
Architecture Teardown
Multi-agent pipeline blueprints with component hours and MGT analog links.
Run a teardown→
From the blog
Related reading
AI Automation for Small Business: What Actually Works
Cut through the hype. Real automation workflows that save hours per week, with cost breakdowns and implementation timelines.
Read articleAI Agents in a Solo Dev Workflow
How Claude Code, MCP servers, and autonomous agents let one developer ship what used to take a team of five.
Read articleMission Control: Building a Cron Registry for a Solo Dev Empire
Centralized job scheduling, heartbeat monitoring, and execution history across ten projects from one admin panel.
Read article