Four things I build. Scoped per project.
I’m one senior engineer, not an agency. Every engagement starts with the problem in numbers and ends with an audited run. Timelines below are common delivery windows; the final timeline depends on integrations, review requirements and existing infrastructure.
AI systems
Agents, LLM pipelines, vision, structured outputs.
- Multi-agent workflows with typed shared state and QA agents
- Generation pipelines with deterministic validation and capped retries
- Document intelligence for PDFs, scans and messy inputs
- Rescue of failing agent prototypes
Typical scope: 2–6 weeks · Proof: LeadForge, Creative pipeline, Document intelligence
Automation
n8n, APIs, webhooks, CRM, WhatsApp and inbox.
- AI inbox and DM handling with human approval before send
- Lead enrichment, scoring and routing into your CRM
- Scheduled reports, sheet-driven bulk jobs, filing and follow-ups
- Quote and RFQ drafting from email or PDF
Typical scope: 3 days – 2 weeks · Proof: Analytics agent
Data systems
ETL, SQL, reconciliation, BI-ready datasets.
- Platform ingestion (ShipHero, Shopify, GraphQL APIs) into SQL Server
- Stored-procedure silver and fact tables
- Parity audits against legacy systems, column by column
- Power BI-ready datasets
Typical scope: multi-week, custom · Proof: E-commerce ETL
AI products
SaaS, async GPU inference, customer-facing AI.
- Next.js + FastAPI products with queued jobs and polling
- Self-hosted open-weight models on RunPod GPUs
- EU-resident, hardened infrastructure where residency matters
- Three-service architectures that scale the expensive part alone
Typical scope: 4–8 weeks · Proof: DentaSmile AI
Every build can include a monthly retainer: monitoring, small changes and tuning on a system designed to run reliably in the first place. Ads and demand generation are covered by the Betterlab partnership.