Brilworks Software

Data comes first and the AI agent comes second in the way this engineering firm organizes its work. Brilworks calls itself a data and AI engineering company, and it argues that an agent is only as good as the information feeding it: stale, duplicated or unreliable data, in its words, produces confident mistakes instead of useful answers.

Foundation first, agent last

The firm describes a sequence it applies to each project. It begins by capturing data from every source, including applications, APIs, files and legacy databases. It then builds pipelines that are cleaned, tested, scheduled and monitored, and a warehouse that serves as a single source of truth the team can query. Only after that does it build the production AI that draws on this data. The company says most teams do it in the opposite order.

What it builds

• Data engineering: ingestion, transformation and a modeled warehouse, using ETL and ELT approaches with Databricks and dbt.
• Data quality and observability: tests, alerting and lineage tracking that catch bad data before it reaches a dashboard or an agent.
• AI agents: agents and LLM applications that answer from the client's own warehouse rather than from a generic model, including retrieval-augmented generation, MLOps and model integration.
• Analytics and business intelligence: dashboards and a metrics layer, so every team works from the same figures.

The firm also lists engineering at the edge and a range of work around the data itself.

Two ways to work with the firm

Clients can choose a fixed-scope project, in which one team owns delivery from the first design review through to deployment and a pipeline into production, or they can embed certified engineers in their own team. The embedded engineers work in the client's time zone, inside its repository and daily stand-ups, so delivery can grow without the time spent recruiting. The firm says most clients start with one model and later add the other.

Partnerships and ownership

Brilworks is a certified Databricks partner for lakehouse and AI engineering, and it also lists partner status with AWS and dbt Labs. It says Databricks-certified engineers are on every engagement. Its Databricks work covers lakehouse architecture, Spark and Delta Lake pipelines and production MLOps across AWS, Azure and Google Cloud. The firm states that the client owns the cloud environment, the warehouse and the code, with no lock-in. It suggests starting with a scoped data audit or a focused proof of concept, and it reports a five-star rating on Clutch across 22 reviews.

Earlier product work

The older description of the company was broader. It covered web, mobile and blockchain development, video applications for live and on-demand streaming, secure communication apps, resource-planning and tracking tools, payment applications and email and SMS marketing, backed by a user experience team. The current site has narrowed that to data and AI.