Data and AI solution design
Define requirements, architecture, product scope, technology choices, decision records, and a delivery plan for a new or existing system.
CALMWORKS works with startups and enterprises on data and AI architecture, implementation, and training. We specialise in AI agents, Databricks, data platforms, and data science in production.
We can help define the technical approach, implement the first production version, or work within an existing team to improve delivery. Training and documentation are included where they are useful, so the people responsible for the system understand how it works.
We scope each engagement around the problem, the existing team, and the systems already in place. A project may combine several of the capabilities below.
Define requirements, architecture, product scope, technology choices, decision records, and a delivery plan for a new or existing system.
Design and implement tool-using agents, multi-agent workflows, evaluators, and voice agents, including guardrails, evaluation, observability, and integration.
Design or improve lakehouse architecture, data models, pipelines, quality controls, governance, MLOps, and model serving on Databricks.
Put models and analytics into production with reliable pipelines, experimentation, serving, monitoring, testing, and application integration.
Train teams through focused workshops, paired implementation, technical walkthroughs, code review, and materials based on their own systems.
Create implementation guides, examples, demos, tutorials, and technical content for developer-facing products and platforms.
The scope and duration depend on the work. These are the most common starting points.
Review the problem, user and technical context, constraints, architecture, risks, and implementation plan.
Design and build a defined system or feature with the team, then provide testing, documentation, training, and handover.
Provide senior hands-on support for architecture, implementation, technical leadership, team training, and delivery over a longer period.
Deliverables are agreed at the start of the project and may include the following.
Application code, agent workflows, data pipelines, APIs, templates, infrastructure, tests, and reference implementations.
Architecture diagrams, technical decisions, tradeoffs, delivery sequencing, estimates, and risk assessments.
Workshops, operating guides, implementation notes, paired sessions, and code review for the internal team.
Share the problem, your current technical setup, and the help you need. We will reply with relevant questions and a proposed scope.