Weple

We put AI into your product, not a demo

AI Feature Development

We add AI features like chatbots, document summaries, and auto-classification to your existing service

The gap between a demo that runs well and a feature people use every day is what separates someone who has actually shipped AI from someone who hasn't.

Price · Pricing

You want AI, but you don't know where to start

You want a chatbot, you want documents summarized, you want incoming questions sorted automatically. The direction is clear, but which model to use, how to connect your data, what it will cost, and how to stop wrong answers are not. A demo takes half a day. A feature users trust every day is everything that comes after.

What we do

  • Start with where it earns its keep

    We pick the spots where AI actually pays off first. Not what looks good to have, but the one or two places that genuinely take work off a person's hands.

  • Connecting your own data

    We retrieve the data that should ground an answer, product docs, catalog details, past tickets, and feed it to the model. This is the part that cuts down on answers made up out of nothing.

  • Designing for cost, latency, and wrong answers

    Which model goes where, how caching brings the bill down, how it looks while it's slow, and how a wrong answer gets handed to a person: we decide all of it together.

  • Wired into the product and shipped

    We connect it as a real feature into your existing screens and server, set up key management and usage limits, and ship it as is.

A record of what we added and how

Which model runs where, what the expected bill and latency are, and how wrong answers are held back, written up so you can adjust it yourself later or hand it to another developer as is.

How to start

  1. Share where you want it

    Tell us where you want to add AI and what data you have. Even if it's still vague, we'll work it out with you.

  2. Scope and quote

    Within 24 hours we lay out how far we can take it, what it costs, and what to watch out for.

  3. Build, connect, hand off

    We build the agreed scope, connect it into the product, and hand it off with the write-up of what we added and how.

A good fit for

  • Services with repetitive questions that need a chatbot or auto-reply
  • Teams sitting on documents, reviews, and data with no summary or search over it
  • Anyone who has put off adding AI out of worry over cost and wrong answers

Frequently asked questions

Which AI model do you use?
We don't fix on one. We weigh accuracy, cost, and speed and pick what fits the feature. Commercial models and open models are both on the table.
Does our data leave our systems?
We settle what goes where before we start. There are ways to keep sensitive data from leaving your systems, so we decide that together when we set the scope.
What if the AI gives a wrong answer?
We design on the assumption it can be wrong. We build in ways to show the source alongside the answer, hand off to a person when confidence is low, or have it say it can't answer.

Where do you want to add AI?

Tell us where you want it and what data you have, and we'll start by laying out how far we can take it.

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