Forward-deployed AI engineering
We work inside your team on one real workflow, adapt a Denegra product or build a thin layer on it, and prove the result on your own process before anything grows.
Software alone rarely fits a real workflow. The model is usually not the hard part. The hard part is everything around it: where the data lives, who approves what, and the people who will use it every day.
So we start from your workflow, not from the model, and we stay with your team until the result shows up in your own process.
We sit with your team and map one real workflow: who does what, which systems it touches and where the time goes.
We adapt a Denegra product, or build a thin layer, on that workflow inside your environment.
We run it on your real process and measure the result with you, against the success measure we agreed before we built.
You take it over, or we keep running it.
Start small. See it running. We would rather show a product working on your data than present a slide about it, so every engagement starts with something you can test.
Your questions, your documents, your project code names. You see what the product does, and what it does not.
One department first. At the end, a short report in numbers from your own use.
Where data must stay in-house, our products run on your own servers and your existing security stack.
The people who build the product also deploy it and support it, so answers come from the source.
We start from working software, not an empty repository. Where it fits, the first build is one of our own products adapted to your process:
Our specialists have built with and compared different AI models, so you get the right model for each job, not just the most expensive one. That can be Azure OpenAI, Google Gemini, AWS Bedrock, another OpenAI-compatible service or a model in your own data centre.
Telecom, banking, healthcare and insurance: teams whose work runs on messages, documents and customer data that has to stay inside.
One workflow, one team, and a success measure we agree before we build. We expand only when the first one works.
Inside your environment: your cloud tenant or your own servers, with your access rules. Requests go only to the models you choose.
No. We start from one where it fits the workflow, and build a thin layer on your workflow where none does.
You take it over, or we keep running it. Either way, the next workflow starts only when you want it to.
Send a short note and we will reply with how we would approach it. No deck or pitch call needed first.
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