Stone Rooster Technology Solutions partner

Data Intelligence & AI

We are able to assist your company in preparing your data to utilize AI and advanced data intelligence systems like Databricks to analyze, understand, and leverage large volumes of data for strategic decision-making.

  • Requirements and documentation of legacy systems and data requirements/definitions.
  • Requirements and documentation of Business Capabilities and functionality being provided by the new AI capabilities.
  • Oversight and project management of delivery of the data warehouse and/or AI Platform.
  • Development and QA of the data warehouse and/or AI Platforms.
  • Training and rollout coordination of data warehouse and/or AI Platforms.

AI in Our Development Process

Our developers utilize AI to supercharge their development workflows, while also ensuring safe output with AI guardrails.

  • We leverage AI agents to produce reliable code, faster
  • We use safeguards like an agents.md file with explicit rules, boundaries, technical constraints, style conventions, and test sequences defined that are required for AI task execution
  • We always have human developers peer review all code produced by AI to ensure code quality and that
Stone Rooster Technology Solutions partner
Stone Rooster Technology Solutions partner

AI in our Cart Service

Our cart service ships with an ai-queries module that turns plain English into safe, validated MongoDB queries. The libs/ai-query module translates intent into a query pipeline with sanitization, injection guards, and result caching. The libs/ai-agent adds a LangChain-based agent, backed by any model, that can iterate over tools, inspect schemas, and stream its reasoning steps back to the caller.

Our Admin App ships an in-product chat (/chat). The chat server runs a small router that dispatches each question to one of seven domain agents — carts, orders, products, prices, inventories, reports, and visualization — each backed by its own MCP server bridged in-process for zero-latency tool calls. The result: ask "how many carts over $100 were abandoned last week?" and the agent picks the right tools, runs the query, and streams back both the answer and a live chart — no dashboards to configure, no SQL to write.