Which startups do you work with?
Startups that have already raised, from pre-seed through Series A and later, with 5 to 200 people: B2B software, health and fintech companies, hardware and consumer brands. We do not take idea-stage or unfunded projects. The products differ, but the problem is the same: a team already using AI everywhere, and source code and customer data that need an approved tool and a written policy.
Can our engineers use AI coding assistants on our codebase?
Yes, under a written rule. Use business or enterprise tiers that do not train on your code, decide which repositories and secrets are off limits, and keep human code review on every AI-written change. Most teams already use these tools, so the work is putting the rules in writing and checking each vendor's data terms, not starting from zero.
Our enterprise customers keep asking about AI in security questionnaires. Can you help?
Yes. Security questionnaires and SOC 2 reviews now routinely ask which AI tools touch customer data, what those vendors retain, and whether a policy exists. The assessment produces the AI usage policy, the approved tool and subprocessor list, and the data map that answer those questions, so the next review takes an afternoon instead of a week.
Do investors care whether we have an AI policy?
Increasingly, yes. Diligence questions about where customer data goes, which AI vendors you rely on, and who owns AI-assisted code are becoming standard. A written policy and vendor inventory answer them cleanly, and the same documents serve your board and your customers.
Who owns code and content our team writes with AI?
Your company, as far as anyone can own it, provided your employment and contractor agreements assign the work and your AI vendors' terms leave output rights with you, which we check. U.S. copyright protects human authorship, so material generated with no meaningful human contribution may not be protectable on its own. The practical answer is human review and editing of anything that matters, and a policy that says so.
Does the CCPA apply to an early-stage startup?
Only once you cross one of its size thresholds, which many early startups have not. That does not leave customer data unregulated: your customer contracts and data processing agreements usually bind you to specific rules about subprocessors and retention, and those cover AI vendors too. The assessment maps which obligations actually apply to you today and which ones arrive as you grow.
Should we hire an AI engineer instead?
Eventually, maybe. Before product-market fit, a full-time AI hire is expensive runway for work that comes in bursts. We set up the policy, the tools, and the first AI features with a fixed quote, and the code and documentation we leave behind give your first AI hire a running start rather than a cleanup job.
Can you build AI features into our product?
Yes. Custom Engineering Solutions covers agents, retrieval over your own data, integrations with your stack, and private model deployments when customer data cannot go to a third-party API. Each project has a fixed quote and a written spec, and your company owns the code.
Do you work with startups outside Orange County?
Our team is based in Irvine and most clients are in Orange County and greater Southern California, where we can train your team in person. Remote engagements work fine for the assessment and On-Going Support.
Where do we start?
A price range from our two-minute quote form, a 30-minute kickoff meeting over video or in person, a written proposal, then the on-site AI Strategy & Assessment: AI tool and vendor inventory, source code and customer data flow review, a written AI usage policy, and a prioritized roadmap.
