Product AI capabilities
Add AI into existing products.
Most products we see don't need a new AI product. They need AI features that make the existing product better.
An analytics tool already has great dashboards and filters. Adding an “ask your data” chat box doesn't replace the dashboards. It gives the non-technical half of the company a way to get answers without pinging an analyst every time. The feature sits inside the same workspace the team already uses, and the business gets to ship something new without touching the reporting engine underneath.
We usually start from the same question. Which part of your product would be faster, cheaper, or more valuable if AI handled a chunk of it? The answer is rarely “all of it.” Usually it's a specific step. Summarizing something long. Extracting something structured. Suggesting a next action. Personalizing a response. Those are the features that ship.
The common mistake is picking the wrong part. Teams often pick whatever is most demo-friendly, not what actually earns its place. A chat widget on a marketing page is demo-friendly. A summarizer that saves a support agent 40 seconds per ticket is boring but pays back in week one.
What we do here:
- Pick AI features that have a real user problem behind them.
- Build them to ship in weeks, not quarters, using existing cloud and model providers.
- Wire them into your product's auth, analytics, and support flows so they feel native.
- Add the evaluation and guardrails so they don't break the first time a user does something weird.
- Hand them off with a runbook your team can maintain after we leave.
We've built AI chat for document workflows, generation tools inside media platforms, and smart routing inside support apps. Each one started with the same conversation: what's the one job your users do today that an AI feature could make noticeably better?
The goal is never “we added AI.” The goal is a feature someone actually uses more than once.