Case Studies
Real businesses, real solutions. Just some of the ways we helped turn heavy repetitive work into systems teams actually use.
Case 01
RFP Agent
IMPACT
ABC Construction can now pursue 5x as many RFPs per year, unlocking $130M in additional annual bid capacity without adding a single person to the team.
PROBLEM / WHAT RUBY BUILT
ABC Construction's RFP process took over 200 hours to complete a single proposal because of manual drafting, scattered source material, and repeated stakeholder interviews.
Ruby built an RFP agent that reads incoming requests, drafts full responses in ABC Construction's exact tone and style, identifies missing or incorrect information, and interviews the right people to complete the proposal.
The agent turns each completed proposal into reusable knowledge, making the next RFP faster and more accurate.
CAPABILITIES
Case 02
Consulting Company Brain
IMPACT
Drastically reduced research time and increased the firm's ability to support new work with proven results from past client cases.
PROBLEM / WHAT RUBY BUILT
A consulting company had valuable knowledge spread across past deliverables, client notes, internal documents, and individual team expertise. Ruby built a company brain that made the firm's knowledge searchable, reusable, and available inside daily client work.
Instead of rebuilding context from scratch for every engagement, consultants could pull from the firm's prior work, reuse proven thinking, and move faster across client projects.
CAPABILITIES
Case 03
Company AI Cohort Training
IMPACT
Trained 40 employees across six cohorts, turning AI from an isolated experiment into a company-wide operating capability.
PROBLEM / WHAT RUBY BUILT
The company wanted employees to use AI inside real workflows, not just experiment with generic chatbot prompts. Ruby trained 40 employees across six cohorts, teaching teams how to apply AI to the work they already do every day.
Each cohort focused on practical workflows: research, writing, documentation, client communication, operations, and repeatable internal processes. The result was company-wide adoption instead of isolated AI usage by a few early adopters.
CAPABILITIES
"AI should make people feel more capable, not replaceable."
Ruby