AI Accelerators
Don't start AI from a blank page
Fully custom sounds better than it is.
The reality is that most enterprise AI use cases, document processing, customer service, supply chain visibility, financial analysis, share the same underlying architecture, even across different industries. What differs is the data, the terminology, and the governance requirements.
Our Approach
Working systems, not slide-deck concepts.
After years of delivery across regulated, data-intensive industries, Datapao has built a library of production-tested AI accelerators: working solutions to problems we have already solved, ready to be configured to your data, your terminology, and your environment.
Every accelerator sits on the same governed, production-grade foundation, which means faster time to value, lower delivery risk, and a starting point grounded in what has actually worked elsewhere.
Configured, not generic.
The underlying architecture, evaluation framework, and governance model are proven and reusable. The data sources, business logic, and outputs are built specifically for your environment. You are buying a solved architecture, not a packaged product.
Governance is not what gets skipped to go faster.
Every accelerator inherits full Unity Catalog governance, AI Gateway orchestration, and structured evaluation by default. Accelerated delivery without skipped controls is the whole point, because an ungoverned fast pilot cannot become a production system.
Days, where the foundation already exists.
Because the architecture is already built and proven, accelerator engagements move dramatically faster than ground-up builds. For agentic use cases, domain-specialised deployments in less than a month is a realistic benchmark rather than a marketing claim, once the underlying platform and data foundation are in place.
Start with a defined scope.
Ship something real.
LLM PoC on Databricks
Applied LLM on Databricks
ML Forecasting PoC
MLOps Buildout
Deep Research Agentic AI on Databricks
Match, configure, pilot, scale.
Every accelerator has real production behind it.
Common questions before getting in touch.
What is an AI accelerator, and how is it different from a custom AI solution?
An AI accelerator is a pre-built, proven foundation for a specific type of AI solution. Instead of developing everything from scratch, we start with an existing architecture, evaluation framework, and governance setup, then configure it to your data, business logic, and requirements. You get a solution tailored to your organisation without paying to rebuild components that have already been developed and tested.
How do I know which AI accelerator is right for our business?
We start with a focused conversation about your use case, existing data, technical environment, and business objectives. From there, we assess which accelerator best fits your requirements and what configuration would be needed. If none of our existing accelerators is suitable, we'll tell you and recommend a more appropriate approach.
Can AI accelerators be customised to our data, industry, and workflows?
Absolutely. While the underlying architecture and reusable components are already established, the solution is configured around your organisation. That includes connecting your data sources, adapting business logic and terminology, integrating with existing systems, and aligning governance with your security requirements. The goal is to accelerate delivery without compromising on relevance or usability.
Do we need an existing Databricks environment to use an AI accelerator?
Our accelerators are built specifically for Databricks. If you already have a Databricks environment, we assess its readiness and build on your existing infrastructure. If you're new to the platform, we can help establish the necessary foundation before deploying the accelerator. We'll identify any infrastructure or data preparation requirements during the initial assessment.
