Automate complex business operations without hiring more hands.
Background pipelines that ingest data, reason with AI, orchestrate tools, and synchronize your business systems reliably.
What I can build.
- ✦Inbound Lead Triage & Strict 5-Minute SLA Enforcement
- ✦Automated Invoice & Receipt Parsing (OCR to Accounting)
- ✦Multi-Platform Content Scheduling & Publication Engines
- ✦Automated Email Digest & Customer Notification Dispatchers
- ✦Back-Office Data Extraction & Form Processing Pipelines
- ✦Scheduled Background Workers & Data Reconciliation Jobs
- ✦Human-in-the-Loop Approval & Triage Flows
What you get.
- Non-blocking asynchronous task queues handling heavy processing in background
- Strict deduplication and idempotency keys preventing double-billing or duplicate emails
- Guarded AI reasoning that falls back to standard workflows if an API times out
- Real-time notifications sent straight to Slack or WhatsApp with 1-click action buttons
- Full job lifecycle tracking (enqueued, running, finished, failed) in database
From fast build to complete system.
You don't always need a massive enterprise build. We scope the software to match your exact timeline and stage.
Focused Working MVP
Automate your highest-friction daily workflow in under two weeks.
Production Infrastructure
Decoupled async worker clusters (Celery/Redis) + SHA256 idempotency + semantic caching + automated retry queues + full audit trail.
Keep your current tools. I'll build around them.
Manual cycle times cut from hours to seconds with 100% audit visibility.
Relevant working systems.
Real implementations that demonstrate this capability in production.
ThreadBase
LLM-powered content scheduling platform with async job orchestration, idempotent scheduling, and full audit trail observability.
A production-grade content scheduling platform achieving reliable job execution with complete lifecycle observability, efficient LLM cost management through semantic caching, and secure media delivery via signed URLs.
Inbound Lead Engine
Production-grade async lead processing with AI intent inference and SLA enforcement.
Full-stack containerized environment. Zero ingestion wait-time. Automated state escalation for hard failures.
Under the hood.
Architectural details and engineering decisions behind this system.
Idempotent Async Queues
Redis Streams and Celery workers isolate long-running operations from API latency.
Deterministic idempotency keys derived from user ID + payload hash prevent duplicate execution on network drops.
Semantic caching with TTL cuts redundant LLM inference costs by up to 60%.
Have a use case for automation?
Tell me what you're trying to solve. I'll outline the architecture and build a working system quickly.