Industry

Software & Product Companies

Data roadmaps, first production models and generative features for product teams that want AI in the product without building a data team first.

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Your first AI feature, shipped.

Product companies feel the pressure to add AI and rarely have the team to do it well. The typical result is a feature built on a vendor API, shipped without evaluation, and quietly switched off when the cost or the complaints arrive.

We take a different route. First a short assessment of where AI actually pays off in your product, ranked by value and how hard it is to build. Then the first feature, built alongside your engineers: a model or an assistant behind your API, with an evaluation suite that scores every change, monitoring for quality and cost, and documentation your team can extend without us.

We have done this for a software house adding machine learning to its clients’ products, for an analytics company that needed to know which use cases were real, and for a consumer app that wanted an assistant grounded in live data. Our own products, from YT-Pings to BestShot.ai, run on the same stack we bring to yours.

Roadmap before code

A ranked list of AI opportunities in your product, scored on value and feasibility, before anyone opens a notebook.

Models inside your product

Features that ship behind your API, with evaluation, monitoring and cost per request handled from day one.

Your engineers keep it

We pair with your team, the code lives in your repositories, and the runbook is written for them.

Where AI pays off in software & product companies.

AI feature discovery

Which parts of your product benefit from prediction, ranking or generation, and in what order to build them.

Recommendation and ranking

Relevance models for search, feeds and suggestions, tuned to the metric your product team already tracks.

Extraction and classification

Documents, tickets and content turned into structured data with confidence scores your code can act on.

Assistants in the product

Retrieval-grounded assistants over your own content, with citations, permissions and a human fallback.

Analytics foundations

The event pipeline and warehouse that make the first model possible and the tenth one cheap.

Independent model review

A second opinion on a model your team or a vendor built. Accuracy, cost, risk and maintainability.

Work in this industry.

Described the way the client experienced it. Ask us for the numbers on a call.

HelloWorld PC

Problem

A software company needed a data roadmap and first machine learning features for client-facing products, with no data team in-house.

Outcome

Roadmap, data architecture and two models that shipped inside client products.

Ensight

Problem

An analytics stack that had grown by accident and no clear view of which machine learning use cases were feasible.

Outcome

A scoped proof of value on real data that the team carried forward into production.

RotoGPT

Problem

Fantasy football players wanted expert advice grounded in live statistics and news.

Outcome

A conversational assistant over live data that answers in seconds with its reasoning shown.

Solutions and products for this industry.

Data Science & AI Consulting

A clear path from the data you have to the first models in production, delivered by the people who build them.

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Generative AI

Language models wired into your documents, systems and workflows, with guardrails and measurement built in from day one.

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Live

YT-Pings

Turn YouTube subscriptions into notifications on email, Telegram, Discord, Slack, SMS or WhatsApp, with AI summaries.

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Working in software & product companies?

Tell us about the problem. We will tell you where we have solved something like it and what it would take.

Get in touch contact@dataminds.gr