AI Agent Development & Implementation
I build autonomous AI agents and agentic workflows that run in production — not just demos.
I'm Almog — a hands-on Fractional CTO and Senior Software Engineer with 15+ years building production software for startups and scale-ups. I now take on a focused number of AI agent implementation projects per quarter, from scoped builds to full agentic system design.
Projects range from $5,000 to $30,000. If you're past the "should we use AI?" stage and ready to build, let's talk.
What I Build
Autonomous AI agents
Custom agents that perceive, decide, and act — handling complex multi-step workflows without constant human input.
RAG systems & AI co-pilots
Retrieval-Augmented Generation pipelines that give your AI grounded, accurate answers from your own data.
Agentic workflow automation
End-to-end automation connecting your CRM, databases, APIs, and communication tools into intelligent pipelines that run themselves.
LLM integration & API orchestration
Connecting OpenAI, Claude, Gemini, or open-source models into your existing product. Function calling, tool use, streaming — production-grade.
Multi-agent systems
Coordinating multiple specialized agents in parallel — task decomposition, routing, error recovery, observability. Built for reliability at scale.
How I Work
I don't hand off a spec and disappear. I architect, code, review, and ship alongside you. Every engagement starts with a scoping call where we define outcomes, not just features.
Typical engagement flow:
- Discovery call — understand your workflow, data, and goals (free, 30 min)
- Scoping document — architecture overview, tech choices, timeline, and fixed price
- Build phase — iterative delivery with weekly check-ins
- Handover — documented, tested, deployed — and you own it fully
What I Bring to an AI Agent Project
- Production mindset — I've shipped AI-powered SaaS (DogBase, Lineups, ArDrive) and know where agents break in the real world: hallucinations, cost overruns, flaky tool calls, observability gaps
- Full-stack depth — I handle the agent layer and the infrastructure around it: APIs, databases, auth, deployment, monitoring
- LLM-agnostic — I recommend the right model for your use case, not the one I'm most comfortable with
- Firestore, GCP, Cloud Run, Vertex AI — deep experience on the Google Cloud stack, if that's your home
- n8n automation — self-hosted workflow orchestration for teams that want power without per-seat SaaS costs
Common Use Cases
- Customer support agent with escalation logic and CRM integration
- Internal knowledge assistant trained on your documentation
- Lead qualification and outreach automation agent
- Data extraction and processing pipeline from unstructured documents
- AI co-pilot embedded in an existing SaaS product
- Operational agent replacing a recurring manual workflow (reporting, scheduling, triage)
Trusted by
Project Investment
All projects are fixed-price after scoping. No hourly surprises.
What clients say
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Ready to build something that actually runs?
I take on 2–3 AI agent projects per quarter. If your timeline is within the next 60 days, reach out now.