Software and SaaS — AI, data & automation
For software product companies whose roadmap needs AI features or more delivery capacity. We add AI inside your product, build new AI products, fix the data underneath and extend your team.
A practical delivery view
A roadmap that outruns the team
If your customers are asking for AI inside the product they already pay for, your roadmap now carries features your team may never have built before. Hiring data scientists and AI engineers takes time and management attention, and the backlog does not wait. The data those features need is often spread across services and old schemas. This page is for founders, CTOs and product heads at software and SaaS companies who need AI features shipped, or more delivery capacity, without stalling the core roadmap.
- AI features customers are asking for
- Skills that are slow to hire
- Data spread across services
- A core roadmap that cannot stall
AI inside your product, and new AI products
We build AI features inside existing products, so your users get the new capability where they already work and do not switch tools. Our healthcare modules show the pattern: plug-and-play, customised per client and added inside the system already in use. We also build new AI products from the first version onwards. The work covers custom AI, agentic automation, voice and language AI and computer vision, in Python, JavaScript and C#, with other tools chosen per project.
- AI features inside your existing product
- New AI products
- Custom AI, agents, language and vision
- Python, JavaScript and C#
Data foundations and extra capacity
AI features depend on the data beneath them, so we also do the data engineering: ETL pipelines, data transformation and migration. When the constraint is people, we add capacity. That can be engineers working alongside your team on a time-and-materials basis, or a whole team built for you and handed over on a build-operate-transfer model. Our two co-founders are practising data scientists with 9 and 10 years of experience, and they stay hands-on in the work.
- ETL pipelines, transformation and migration
- Engineers working alongside your team
- Whole teams on build-operate-transfer
- Founders who stay hands-on
Your product, your decisions
The aim is for our work to ship the way the rest of your product does: through your reviews and your release process. Your product and engineering leads keep ownership of the roadmap, the architecture and what reaches users. For clients in the United States and Europe, the team works with agreed hours of overlap with your working day. Client data is handled only with your explicit permission, under a strict no-retention policy, and never shared with third parties. Personal information is kept out of what an AI model is given.
- Ships through your reviews and releases
- Your leads own roadmap and architecture
- Agreed overlap hours for the US and Europe
- No retention of client data
What this has looked like in delivered work
For EHR product owners, we built six healthcare AI modules that sit inside their existing systems. ADAM OS, a platform we built, runs for a partner network with 100+ dealer partners across 500+ locations. For a leading insurance group, we migrated databases dating from 2003 to a modern, scalable ETL pipeline at petabyte scale, with zero production downtime, within 4 months of project start. We have also built and handed over two centres with 80+ people each. These results belong to those engagements and are no forecast for yours.
- Six AI modules inside EHR products
- ADAM OS: 100+ dealer partners, 500+ locations
- Petabyte-scale migration, zero production downtime
- Two centres of 80+ people handed over
Start with one feature or one gap
Bring one item from your roadmap: an AI feature customers keep requesting, a product idea, a data problem that blocks it, or a team you cannot staff. We will tell you how we would approach it and which way of engaging fits: time-and-materials, outcome-based or build-operate-transfer. The first conversation carries no commitment. You can also answer six questions on this website and receive a free written AI readiness report within one business day.
- One feature, product idea or data problem
- A choice of three ways to engage
- Free AI readiness report within one business day
Questions that come up
Will our users have to switch to a new tool?
No. We build AI features inside the product your users already work in, so the new capability appears where they are. We took the same approach with our healthcare modules, which were added inside the systems people already used.
How do you engage with product companies?
In three ways: time-and-materials contracts, outcome-based contracts, or build-operate-transfer, where we build a team for you and hand it over. For clients in the United States and Europe, we agree hours of overlap with your working day.
Are the founders involved in delivery?
Yes. Both co-founders are practising data scientists, with 9 and 10 years of experience, and they stay hands-on. Data Prophets was founded in 2019 and has served 300+ customers.
Can you build a whole team for us?
Yes. On a build-operate-transfer model we build the team, run it and hand it over to you. We have built and handed over two such centres, each with 80+ people. The size and shape of a team for you would be agreed case by case.
Let’s talk about your next step.
The workflow, the data and what needs to change.