Drafting, summarizing, and personalizing built directly into your existing product or workflow. $3,999/mo retainer.
- Scope
- Build
- Evaluate
monthly retainer
Who this is for
You already have a product, a website, or an internal tool, and the gap is not a new system, it is a missing capability inside the one you have. I integrate generative AI directly into what already exists: a draft-writing feature inside your app, a summarizer inside your dashboard, personalized copy inside your existing send flow, instead of asking you to adopt another separate tool.
The pain today
- A separate AI tool means copying results back and forth into the system that actually matters
- Generic AI writing tools ignore your specific voice, format, and existing data
- Adding an AI feature risks breaking the parts of the product that already work
- No one available to own an integration that touches production code
- Vendor AI add-ons stop at their own product boundary and cannot reach your data
The outcome you get
- Generation built into the screen or workflow where the work already happens
- Output shaped by your existing data and formatting, not a generic template
- Integration tested against your current product before anything goes live
- One senior engineer accountable for the whole integration, not a hand-off chain
- Code and documentation yours from day one under Work Made for Hire terms
Built into what you already have, not a separate product
Most generative AI vendors sell a standalone tool: a separate login, a separate interface, a separate place to copy results out of and paste them back into the system that actually matters. Integration means the opposite. The generation happens inside the screen where the work already occurs, using the data already sitting in that screen, and the output lands directly where it needs to go.
That is a different engineering problem than standing up a new AI tool. It means reading your existing data model, respecting your existing permissions, and delivering a feature that looks like it always belonged there.
Generation built into the screen or workflow where the work already happens
Where this actually earns its place
Not every feature benefits from generation, and adding it everywhere dilutes the cases where it genuinely helps. The pattern I look for: a task where a first draft, a summary, or a rewrite saves real time, and where a person still reviews the result before it goes out. Drafting a first-pass reply, summarizing a long record into three sentences, personalizing a template with real account data, these hold up. Fully automated output with no review step in a context where accuracy matters does not, and I will say so before building it.
2M+: Records processed.
Working inside your existing systems
I work with Next.js, Node.js, and TypeScript on the application side, and PostgreSQL or MongoDB for the data underneath, matching whatever your product already runs on rather than asking you to migrate. OpenAI and Claude both handle generation well; the choice depends on your content type and existing budget, tested against real examples from your product before anything is committed.
One integration I delivered connected four separate source systems into a single HubSpot destination for one of Brazil's largest veterinary networks, processing over 2,000,000 records with each sync completing in under 50 seconds. That is the same integration discipline generative AI work needs: know the data model cold before touching a single field.
Keeping a human in the review loop
Generated output that goes out unreviewed is a risk multiplier, not a time saver, whenever the content carries real consequences. I build a review step into every integration by default: a draft lands where a person can see it before it sends, publishes, or writes to a record. Where the stakes are genuinely low, that review step can loosen over time as confidence builds; it never starts loose.
Pricing, delivery, and ownership
Generative AI integration runs under the AI Development retainer at $3,999 a month, delivered in cycles of two to four days with daily async updates and a response inside 24 hours. The engagement carries a 14-day money-back guarantee, and you can cancel anytime after. The code, the integration, and the documentation are yours under Work Made for Hire terms from the day you pay.
Recent proof
A comparable engagement, delivered and documented.
Four systems, one source of truth: HubSpot visibility for one of Brazil's largest vet networks
Built a custom integration layer connecting four source systems into HubSpot for one of Brazil's largest veterinary companies. Leads sync in under 50 seconds.
Read the case studyRelated services
The same work, framed for a different situation.
Frequently asked questions
The questions prospects ask before they book.
No. Integration means building the capability into what you already run, not replacing it. The application, the data, and the workflow stay the same; what changes is that a generation step now lives inside them.
OpenAI or Claude, chosen based on your content type and tested against real examples from your product before either is committed to. I do not default to one without checking it against your actual use case first.
I test against your current product before anything goes live, and I work inside your existing data model and permissions rather than bolting on a separate system. The goal is a feature that looks like it always belonged, not a fragile add-on.
That is fine. I read the existing product myself before proposing anything, and the whole engagement is scoped so you are not required to have technical staff of your own to manage it.
By default, a review step is built in wherever the output carries real consequences: the draft lands where a person sees it before it sends, publishes, or writes to a record. That can loosen over time once accuracy is proven, but it never starts loose.
The AI Development retainer is $3,999 a month, with a 14-day money-back guarantee and the option to cancel anytime after. Work lands in cycles of two to four days rather than a single delivery months out.