AI systems that run your operations, not just answer questions.
I turn scattered business data — emails, contracts, spreadsheets and internal databases — into proactive, SLA-driven management tools, built on secure RAG and multi-agent pipelines with a human approving every action.
For CEOs, COOs and operations, procurement and HR leaders.
- Your data never trains public models
- Answers cite their sources
- Human approval on every action
- Role-based access control
AI as operational infrastructure — not magic.
Most AI offerings are chatbots and quick automations. Serious operations need systems that are grounded in your data, auditable, and safe to trust.
Typical AI automation agency
- Generic chatbot wrapped around a public API
- Answers that sound right, with no sources
- AI acts on its own with no approval step
- Unclear where your data goes
- Promises of "10x growth"
AI Architect for Business
- Architecture designed around your real workflows
- Every figure traced back to a source document
- AI drafts and flags — your team approves
- Private deployment, access control, audit logs
- Scoped deliverables with measurable KPIs
Three engineering principles behind every system.
I don't hide how the systems work. These standards are what make them reliable enough for real operations.
Retrieval-Augmented Generation
The AI reads your actual contracts, financials and records — and cites them. If an answer isn't in your data, the system says Not found instead of guessing. Designed to minimize hallucinations and make every claim verifiable.
AI as analyst, human as decision-maker
AI is a poor autonomous executive but a brilliant analyst. The system drafts actions, flags bottlenecks and prepares communications — a person always clicks Approve before anything is sent or changed.
Multi-agent pipelines
Not one chatbot doing everything. Specialist agents — Analyst, Drafter, Controller — each do one job and cross-check each other before any result reaches your screen.
Every answer either carries a source or is explicitly refused. Every action waits for a human.
Clear deliverables, not open-ended consulting hours.
Start with an audit, then build what the audit proves is worth building.
Automation-Fit Audit
I analyze how your team works, map where your data lives, and deliver an architecture blueprint showing exactly where AI will remove wait times and bottlenecks — and where it won't.
- Workflow & bottleneck mapping
- Data-source inventory and readiness check
- Prioritized use cases with expected impact
- Architecture blueprint, costs and roadmap
Proactive Management Desk
A live desk — for suppliers, HR talent, sales or customer operations — that pulls unstructured data into one place, tracks SLAs in real time, and drafts the follow-up actions your team should take each morning.
- Unified view across emails, files and systems
- Real-time SLA and deadline tracking
- Drafted actions with one-click approval
- Cited figures, honest gaps
Enterprise RAG Pipeline
A secure system that reads long contracts, policies or technical documentation and answers complex operational questions with cited, verifiable sources.
- Private deployment on your cloud
- Table-aware processing of legal & financial docs
- Role-based access to sensitive content
- Accuracy evaluation before go-live
Where operational AI pays off first.
Supplier Desk
Tracks deliveries, contract terms and SLA penalties across vendors; flags breaches and drafts the follow-up email for approval.
HR Talent Desk
Brings candidates, interview feedback and hiring deadlines into one view, and prepares next-step messages for recruiters to approve.
Contract Intelligence
Ask "What's our termination notice with Vendor X?" and get the exact clause, cited — or a clear "not found".
Service Escalation Desk
Monitors tickets and emails for at-risk customers, summarizes context, and drafts responses for agents to review.
Built for data you can't afford to leak.
Security is part of the architecture from day one — not an add-on.
No training on your data
Enterprise model agreements and private deployments, so your data is never used to train public models.
Role-based access control
People and agents only see the documents and fields their role allows.
Table-aware chunking
Financial tables and legal clauses are processed with structure intact, so numbers stay accurate.
Source citations
Every answer links back to the document and passage it came from.
Audit trail
Every AI suggestion, approval and action is logged and reviewable.
Your infrastructure
Deploy in your own cloud environment where required, with your existing identity provider.
How we work together.
Intro call
30 minutes on your operations, goals and data. No cost.
Audit
Two-week Automation-Fit Audit and architecture blueprint.
Build
Pilot on one workflow, measured against agreed KPIs.
Scale
Roll out, train your team, and extend to new workflows.
Itay Gantz
I'm an AI solution architect. I help organizations move from "we should be using AI" to AI systems that run inside daily operations — grounded in their data, governed by their people, and measured by business results.
My work sits between the business and the technology: understanding how operations actually run, then architecting RAG pipelines, multi-agent workflows and management desks that fit them — including complex, multi-vendor and international projects.
Common questions
What is an AI solution architect?
An AI solution architect designs how AI fits into your business end to end: which problems to solve, which models and data to use, how systems connect, and how security, accuracy and cost are controlled — then oversees the build.
What is RAG and why does it matter for my business?
Retrieval-Augmented Generation means the AI answers from your own documents and data instead of its general training. It lets every answer cite a source, and lets the system say "not found" when the information isn't there — essential for contracts, finance and operations.
Will AI take actions on its own?
Not by default. The systems I build draft, flag and prepare; a person on your team approves before anything is sent or changed. Automation levels can be raised gradually where you're comfortable.
Is our data safe?
Yes — systems use enterprise model agreements or private deployments where your data isn't used for training, with role-based access control and full audit logs.
Why start with an audit?
Because the most valuable AI projects aren't always the obvious ones. The two-week audit makes sure you invest in workflows with real, measurable impact — and tells you honestly where AI isn't worth it.
Find out where AI will actually pay off in your operations.
Start with a free 30-minute intro call. You'll leave with a clear view of whether an audit makes sense for you.
- Reply within one business day
- No obligation
- NDA available on request