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Why companies hire a fractional AI CTO
Most small and mid-size companies now have more AI ideas than they can judge: a support assistant, document processing, an internal search over their files, an agent that updates the CRM. What they lack is a senior person who can say which of these will pay for itself, what each will cost every month, and how to build it without sending customer data where it should not go.
A fractional AI CTO fills that gap one or two days a week. At Lytvynov Production this is Anton Lytvynov, who holds a master's degree in artificial intelligence and leads the LLM, RAG and AI agent projects our team builds for clients.
What the fractional AI CTO decides
Which use cases
- Collects the AI ideas across the company and scores them by value, feasibility, risk and running cost.
- Kills the ones that only look good in a demo, and picks one or two to build first.
Build, buy or wait
- Compares off-the-shelf tools with a custom build for each use case.
- Chooses models and providers (OpenAI, Anthropic, Google, open models) per task, not per fashion.
Costs
- Estimates cost per request and per month before anything is built, using the same method as our LLM API cost calculator.
- Sets up caching, batching and model choices that keep the bill predictable; see what OpenAI and Claude APIs really cost.
Data and risk
- Writes the rules for what data may reach which model, where personal data is masked, and what is logged.
- Defines how answer quality is measured with a test set of real questions before launch.
Delivery
- Writes the brief for developers or an AI vendor, reviews their estimates and code, and signs off releases.
Typical first 90 days
| Period | Work | Result |
|---|---|---|
| Days 1-30 | Inventory of AI ideas, systems and data; interviews with the teams that would use AI | A scored list of use cases, a recommended first project, cost estimates, data rules |
| Days 31-60 | Brief and vendor or team choice; prototype of the riskiest part against real inputs | A tested prototype and a fixed scope for the first build |
| Days 61-90 | Build oversight, evaluation set, launch plan | The first AI feature live or close to it, with measured quality and a known monthly cost |
Who it is for
- Companies with 10 to 500 people that want AI in their product or operations and have no senior AI or engineering lead.
- SaaS products whose customers expect AI features and whose team has not shipped LLM features to production yet.
- Companies that already pay for AI tools or an AI vendor and are not sure the money is well spent.
If you only need a one-off plan, our AI consulting assessment may be enough. If you already run AI features and want them checked for quality, cost and security, see the AI audit.
Price
| Plan | Price |
|---|---|
| AI CTO 1 day a week | $2,500 / month |
| AI CTO 2 days a week | $4,500 / month |
| One-off technical audit of an existing product | $3,500 fixed, 2 weeks (details) |
The CTO work is billed separately from development, and you are free to build with any vendor. Anton takes at most two fractional clients at a time.
What our team has built with AI
The decisions are grounded in AI products our team has built and runs. Our own SaaS, AI Resume Master, uses LLMs in production, and client work includes an AI companion with RAG memory. For the technical side of what we write about, see Claude vs OpenAI API and the OpenAI and Claude API production checklist.
