Custom AI development
Custom AI built around your data and your workflows
Off-the-shelf AI tools are the right answer more often than most vendors admit. When they are not, Devino's senior engineers build custom AI around your data, your workflows and your rules, and the code is yours.
Get it builtWhat custom AI development covers
AI on your own data
Retrieval over your documents and databases, so the system answers from what your business actually knows.
Workflow agents
Agents for the steps no packaged tool models: document processing, browser automation and ops handoffs, with guardrails and an audit trail.
Custom models
Task-specific models where an API model is not enough: spaCy, PyTorch, OpenCV and fine-tuned LLMs, trained, deployed and monitored.
AI inside your product
AI features wired into the stack you already run, with the product experience around them, or whole AI products built from scratch.
Evaluation you can read
A test set built from your real examples, so you can see whether each change makes the system better or worse.
Custom or off the shelf: an honest read
Custom AI earns its cost when the way you work is the point: a workflow no packaged tool models, data that has to stay in your systems, or an AI behaviour that is the product itself.
It does not earn its cost when an existing tool already does the job, or when there is little data and little volume to justify building anything. The first reply to every brief is an honest read on fit, and that includes saying so when an existing tool would serve you better.
Start with an API model, not a custom one
Most useful AI features are an existing model API plus retrieval over your own documents, careful evaluation and a good interface. That ships faster and is easier to change.
We move to a custom model only when testing shows the API cannot meet the bar, and we show you that evidence. A vendor who proposes training a model first should be able to explain why an API model is not enough.
What custom means in practice
Custom means built on your data, with your examples turned into an evaluation set before anything is tuned. Your data stays in your infrastructure wherever possible, and we document what leaves your systems and why.
The prompts, retrieval pipelines, evaluation sets and any fine-tuned model live in your repository, with tests and docs, so another team could pick the project up without calling us.
What we have built ourselves
Devino builds and runs its own AI products. Shorty summarizes YouTube videos and Spotify podcasts, SuperBooks categorizes bank transactions and matches each one to its receipt or invoice, and GetItDone gives AI agents the same task context a person has.
SuperBooks runs a golden dataset of matching cases in its test suite, so a drop in quality shows up before it ships. That is the kind of discipline we bring to a custom build.
Case studies
SuperBooks — AI bookkeeping for small businesses
AI bookkeeping and accounting software that connects to your bank, categorizes each transaction and matches it to its receipt or invoice.
GetItDone — a task manager your AI can actually see
An AI-native task manager where daily plans, stand-ups, tasks and time tracking live in one place, and AI agents get the same task context a person does.
Shorty — AI summaries for YouTube & Spotify
An AI summarization app for YouTube and Spotify that helps people save time and learn faster — designed in Figma, built with Next.js and Python microservices.
Growing 50% month over month
Frequently asked questions
What are you building?
Three minutes at /start: describe the project. An engineer replies with a scoped plan within one business day, not a sales call.
Get it built