Generative features that belong in a product
A demo that writes a paragraph is easy. A feature your customers rely on every day is the hard part — and that's what we build. We integrate text, image and content generation into your product so it fits your workflow, your brand voice and your data.
We ground generation in your own content wherever possible, so the output reflects your facts instead of the model's guesses. That's the difference between a gimmick and a feature people keep using.
- Drafting and rewriting assistants tuned to your tone and rules
- Content generation grounded in your own documents and data
- Image and asset generation with brand and safety constraints
- Structured output (JSON, fields, tables) the rest of your app can use
- In-product copilots and generation embedded in existing screens
Built responsibly — because the output represents you
Generative models can be confidently wrong, and whatever they produce goes out under your name. We build the controls that keep that from becoming your problem: grounding, review steps, content filters, and clear limits on what the feature will and won't attempt.
For anything customer-facing or consequential, we design a human-in-the-loop path so a person can approve before it ships. We're honest about where generation is a great fit and where it isn't.
- Grounding in your source content to reduce fabricated claims
- Human review/approval steps for sensitive or public output
- Content safety filters and prompt-injection defenses
- Guardrails that keep the feature on-topic and on-brand
- Logging and versioning so you can trace what was generated and why
Cost, speed and model choice under control
Generative features have real per-use costs and latency that add up at scale. We architect for that from the start — caching, right-sizing the model to the task, and falling back to cheaper options where quality allows.
We're not tied to one vendor. We'll pick the model that fits your quality, cost and privacy needs, and build so you can swap it later without a rewrite.
- Model selection matched to quality, cost, speed and privacy
- Caching and prompt design to control per-request cost
- Vendor-flexible architecture so you're not locked in
- Usage monitoring and cost controls built in
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Frequently asked questions
How do you keep the AI from making things up?
You can't get a language model to zero errors, so we don't pretend otherwise. We reduce mistakes by grounding output in your real content, constraining what the feature attempts, and adding review steps for anything that matters. For high-stakes output, a person stays in the loop before it goes out.
Can it match our brand voice and rules?
Yes. We tune the system with your style guide, examples of good and bad output, and hard rules about what it must never say. It won't be perfect on its own, which is why we pair it with review controls for anything public.
Do we have to use one specific AI company's model?
No. We recommend based on your needs and build so the underlying model can be changed later. That protects you on price and keeps you from being locked into a single vendor.