I AM
Segev Sinay,
I design AI systems that transform how organizations work — from multi-agent architectures to enterprise RAG pipelines. Not demos. Production systems.
Agent Architecture · RAG Pipelines · AI System Design
The Shift
AI Is Not a Tool. It's a New Way to Work.
The organizations winning right now aren't using more AI tools. They're redesigning how they operate around AI.
The Reality
Most organizations approach AI the wrong way. They add a chatbot here, automate one email there, try a plugin that nobody uses after week two. Each tool is an island. Nothing connects to how the organization actually works.
The real value of AI isn't in individual tools — it's in systems that connect, learn, and compound. A RAG pipeline that indexes your internal documents into a vector database. An agent that handles document processing, routed to another that classifies and acts. An orchestration layer that understands your business logic. That's when the time savings become real.
A real example: A law firm drowning in document review. Hundreds of contracts, due diligence packages, regulatory filings — all processed manually. The solution isn't "add AI." It's a multi-agent system: one agent extracts clauses, another classifies risk levels, a third cross-references against precedent stored in a vector database — all orchestrated to surface what matters to the attorneys in minutes, not days.
That's what I build. AI architecture that fits your organization — not generic templates, not off-the-shelf tools, but production systems designed around how your team actually operates.
Self-diagnosis
Is Your Organization Ready for AI?
Most organizations don't realize what's blocking their AI progress until they map it out. Check any that sound familiar.
Your Team Is Doing Work AI Could Handle
Manual, repetitive, brain-numbing
Documents get copied between systems. Reports get formatted by hand. Emails get categorized manually. Your team is spending real hours on work that doesn't require their expertise — and it's costing more than anyone tracks.
Knowledge workers spend an average of 40% of their time on automatable tasks
You Tried AI Tools. Nothing Actually Integrated.
Pilot paralysis
ChatGPT, Copilot, a plugin or two. But nothing connects to your actual workflow. Every AI tool is its own island. Your team still switches contexts, still copy-pastes, still works around the tools instead of with them.
80% of AI pilots never make it to production
You Know AI Can Help — But Not Where to Start
Strategy paralysis
Leadership wants a plan. Every vendor has a framework. But the gap between 'AI will transform our industry' and 'here's what we build this quarter' is where most organizations get stuck — indefinitely.
The bottleneck in AI adoption is rarely the technology
Your Knowledge Is Everywhere. AI Can't Access It.
Siloed information
Your organization's knowledge lives in emails, PDFs, Slack, spreadsheets, and the heads of people who might leave tomorrow. When AI needs it, it can't find it. The bottleneck isn't intelligence — it's access.
Most organizations use less than 10% of the knowledge they generate
Every AI Project Is a One-Off. Nothing Compounds.
No AI flywheel
Each automation is a separate experiment. Each agent is a one-time build. There's no shared infrastructure, no learning loop, no system that gets smarter over time. You're spending on AI without building leverage from it.
The real value of AI comes from systems that compound, not standalone projects
Your Competitors Are Moving. You're Still Evaluating.
Speed asymmetry
Competitors are embedding AI into their products, operations, and customer experience. You're still in exploration mode. The gap isn't closing — it's widening every quarter you spend evaluating instead of building.
Early AI adopters are building advantages that compound over time
Check any that sound familiar.
Sound familiar?
“We tried AI tools. Nothing actually integrated.”
The Approach
I Don’t Just Implement AI.
I Redesign How You Work.
Most AI projects fail not because of the technology — but because nobody mapped the actual workflow first. I come in, understand your operations end-to-end, and design AI systems that fit the way your team actually works.
My background is unusual for this field: economics, finance, and a decade building complex software systems. That combination means I think in workflows, constraints, and second-order effects — not just implementation. When I look at an AI problem, I map the process before I touch the technology.
Top of my class in economics. Top of my class in finance. Top of my programming cohort. Different disciplines, same standard. I don’t mention it to impress — I mention it because it tells you something about how I’ll approach your work.
Services
Ways to Work Together
Every engagement starts with your workflow, not my framework. Here's what that usually looks like.
AI System Design
Before building anything, you need to know what to build and why. I map your workflows, identify where AI creates the most leverage, and design the full system — RAG pipelines, vector databases, agent orchestration, and the integration layer that connects it all to your existing stack.
Deliverables
- End-to-end workflow mapping & AI opportunity analysis
- RAG pipeline & vector database architecture
- System design with integration blueprints
- Cost modeling & ROI projection per initiative
Multi-Agent System Design
Complex tasks need specialized agents working together, not one model doing everything. I design hierarchical agent systems where each agent is an expert in its domain — orchestrated to route, delegate, and synthesize results into something your team can act on.
Deliverables
- Agent hierarchy & orchestration design
- Domain-specific agent configuration
- Prompt engineering & optimization
- Integration with your existing systems
Enterprise AI Deployment
You have the AI prototype. Now you need it production-ready — handling real data, real failures, and real scale. I architect systems with multi-provider fallback, evaluation frameworks, cost optimization, and the observability layer that tells you what's actually working.
Deliverables
- Production architecture with fallback & redundancy
- Evaluation framework & quality metrics
- Cost optimization & token budget management
- Monitoring, observability & knowledge transfer
AI Strategy & Assessment
Not sure where to start? I audit your current operations, identify where AI creates the biggest impact, and deliver a prioritized roadmap — including what NOT to automate. Think of it as a technical due-diligence for your AI strategy.
Deliverables
- Operations audit & AI readiness assessment
- Prioritized implementation roadmap
- Build vs. buy analysis per use case
- Team capability gap analysis & hiring plan
Track record
Real Products, Real Results
AI systems, product builds, and architecture overhauls — every project here shipped to production and created measurable impact.
Client feedback
Here’s What My Clients Say
Names withheld under NDA. The problems and outcomes are real.
“Honestly, we almost didn't bring him in. We'd been burned by external help so many times that we'd given up and decided to just grow the team internally. But our timeline forced our hand - we had no choice but to bring someone in from outside to hit our deadlines. And honestly? It completely changed how I think about external help. Segev was fully remote, but more present than people sitting in our office. He shaped our architecture and pushed back on decisions we were sure about. We didn't always understand why he insisted, but then it clicked - he just genuinely cares about our success. As he put it: 'your success is my reputation, so you have to succeed.'”
- Head of Product, Series B Fintech
FAQ
Frequently Asked Questions
Common questions about AI consulting, system design, and how I work with organizations.
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Ready to Work Differently with AI?
I work with a small number of organizations at a time. Reach out to discuss your workflows and see if there’s a fit.