For startups & scale-ups
AI-native from day one, without the science project.
Founders face two AI questions at once: what belongs in the product, and how much of the company can run on agents instead of headcount. We help you answer both with a defensible sequence, ship the first pieces in weeks, and keep your options open on models and platforms.
Two decisions, one budget
The product question and the operations question are different problems. Most startups answer only the first and pay for it in the second.
Investors now ask whether a company is "AI-native". Usually they mean two things at once: does the product use models where they create real advantage, and does the company run lean because agents handle work that used to need people. Both matter for your next round, but they need different plans, different people and different risk appetites.
On the product side, the risk is building a thin wrapper that the next model update makes redundant. On the operations side, the risk is the opposite: spending founder time on tooling experiments while sales, support and finance ops are still done by hand at a scale that no longer justifies it.
We work with founders and their first operators to separate the two, decide what to build, what to buy and what to defer, and then ship the operations pieces quickly. Where a decision needs senior judgement more than a full-time hire, we provide it as a fractional Chief AI Officer.
- Typical companySeed to Series B, 5–150 people
- FormatsTwo-week assessment, six-week pilot, fractional CAIO
- Working modeRemote-first, English or German, on site in Berlin
- OutcomeA sequence you can defend to your board and build with a small team
Where startups usually stand
AI is on the product roadmap, but nobody has decided how much
Feature requests, investor pressure and a competitor's launch have pushed models into the plan. What is missing is a view of where a model actually creates advantage in your product, and where it is a commodity you should buy from an API and move on.
Operations are still manual at a scale that is starting to hurt
Lead qualification, support tickets, invoice chasing, onboarding emails and investor reporting are done by the same three people who are also building the company. Every new hire in these roles is a hire you may not need to make.
Speed matters more than perfection, but so does the burn
You cannot run a six-month strategy programme. You also cannot afford a stack of subscriptions and API bills that nobody reconciles. The plan has to ship in weeks and pay for itself visibly.
Every platform choice made now is expensive to undo later
Early decisions about model providers, agent frameworks, vector stores and automation tools harden quickly. A little architecture discipline at this stage keeps you free to switch when prices, models or your data-residency requirements change.
A Head of AI is premature, but the questions are not
You need someone senior to make platform, governance and hiring calls, and to talk to investors and enterprise customers about how you use AI. A full-time hire at this stage is expensive and hard to find; the need is real either way.
What we do for startups
Everything below is designed for small teams that need to move fast without leaving a mess behind.
Fractional Chief AI Officer
One to two days a week of senior leadership: AI strategy for product and operations, platform decisions, investor and customer conversations, hiring plans and governance. You get the judgement without the full-time cost, and the role hands over cleanly when you hire.
ii.AI agents for your operations
We build the agents that let a small team run sales development, customer support, finance ops and onboarding: ticket triage and reply drafts, lead research and qualification, invoice follow-up, investor updates from your own data. Production-grade, with humans approving what matters.
Two-week AI assessment
A compressed version of our readiness assessment: where AI belongs in your product versus your operations, the three use cases worth building first, and the platform decisions that keep you flexible. Written for founders, readable in an hour.
Six-week pilot to production
One workflow, one owner, one metric. We build it, connect it to your CRM, helpdesk or billing system, measure it against the baseline and hand it over with documentation your team can maintain. See agentic workflows.
Architecture that avoids lock-in
A thin abstraction over model providers, a clear home for your data, evaluation and cost tracking from the first day. It costs little now and saves a migration later. We are vendor-neutral and have no reseller agreements.
Governance that enterprise customers accept
If you sell to corporates or regulated industries, their procurement will ask how you use models, where data goes and what the EU AI Act means for your product. We prepare the answers and the lightweight governance behind them before the questionnaire arrives.
A typical path
Startups rarely need the full programme. The usual sequence looks like this.
Intro call and scoping
Thirty minutes on where you are: product, team, stack, runway, investor expectations. We tell you honestly whether an assessment, a pilot or a fractional role is the right first step.
Two-week assessment
Interviews with the founders and the people running sales, support and finance. We map the operations that eat time, review the product's AI plans and return a short written sequence with platform recommendations.
Six-week pilot
We build the first agent or workflow under production conditions, integrated with your tools, with a measured baseline and a target. Your team is involved from the start so nobody has to take over a black box.
Decide: scale, rent or hire
With one system running and measured, you decide what comes next: more workflows, a fractional Chief AI Officer to keep momentum, or a hiring plan for your own AI team. We help with all three and are equally happy to step back.
Frequently asked questions
Should we build AI into the product or fix operations first?
Usually both, but not at the same pace. Product AI needs product discovery and often data you do not have yet. Operations AI runs on tickets, emails and CRM records you already have, so it ships faster and frees the time you need for the product work. The assessment gives you a sequence for both.
What does "AI-native" mean to investors, in practice?
It rarely means a proprietary model. It means the company has decided deliberately where models create advantage, that operations scale without proportional headcount, and that the founders can explain the cost and risk of their AI use. We help you get to that position and describe it credibly.
We are engineers ourselves. Why would we need outside help?
You can build agents. The scarce resource is time, and the judgement about what to build, what to buy and how to keep it maintainable at your stage. We bring patterns from many deployments, so you skip the six weeks of trying every framework. The code stays yours.
How do you keep us from platform lock-in?
Thin abstractions over model providers, portable data formats, evaluation sets that let you compare models objectively, and a preference for open standards such as the Model Context Protocol. We also tell you when lock-in is a reasonable trade for speed.
When does a fractional Chief AI Officer make more sense than hiring?
When the decisions are frequent and consequential but the workload is not yet a full-time job, typically between seed and Series B. The fractional role builds the strategy and the first systems and helps you hire the person who takes over. Read more on the fractional Chief AI Officer page.
Related services
Fractional Chief AI Officer
A senior AI leader embedded in your company one to two days a week: owns the roadmap, decides on vendors and architecture, runs governance and reports to the board, until you no longer need one.
Custom AI agent development
Single- and multi-agent systems designed and built for production: tool use, memory, MCP servers, evaluation suites, guardrails and EU deployment.
AI readiness assessment
A two- to three-week diagnostic across data, systems, skills, governance, processes and culture, ending in three first use cases and a 90-day plan.
Build or buy AI agents?
Platform agents, low-code orchestration or custom frameworks: a comparison, the cost dimensions that matter, and the hybrid architecture we usually recommend.
Let's find the first workflow worth automating.
A 30-minute intro call, no slides and no obligation. We listen, ask about your processes, and tell you honestly where AI agents would pay off and where they would not.