Normalized claim
Engineering hours saved: 140 hours decrease
a single engineer used Antigravity to manage 11 parallel workstreams and save more than 140 hours of manual effort
Blackroll builds an AI recovery coach with Gemini Enterprise Agent Platform on Google Cloud
Use case typeAI agentsUpdated Jul 1, 2026
Blackroll needed to unify disconnected customer data and build an interactive AI coaching experience that updates guidance based on wearable signals. It consolidated e-commerce records and mobile app events into BigQuery, used Cloud SQL to ingest daily wearable data, and deployed a headless architecture on Cloud Run, Firestore, and Cloud Run functions. Using Gemini Enterprise Agent Platform and Agent Development Kit (ADK), Blackroll built autonomous coaching agents and used Agent Search to ground recommendations in verified scientific research and knowledge from its 5,000 physiotherapists. Antigravity was used to automate software development loops for faster implementation.
Reported outcomes
Software footprint reduction: −20%
Sustainability & resources
Engineering hours saved: More than 140 hours
Catalog median for sustainability & resources deployments: −25% across 23 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Software footprint reduction: 20% decrease
the company has already reduced its software footprint by 20%
Normalized claim
Running costs reduction: 25% decrease
Blackroll expects this platform unification to cut its overall running costs by roughly 25% over the next year
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Blackroll
- Provider
- GCP
- Maturity
- Production
- Linked source
- Google Cloud Customer Stories
It consolidated e-commerce records and mobile app events into BigQuery, used Cloud SQL to ingest daily wearable data, and deployed a headless architecture on Cloud Run, Firestore, and Cloud Run functions
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1AI agents
- 2Customer service agent
- 3Search modernization
- Consolidated customer and behavioral data in BigQuery
- Used Cloud SQL for daily wearable data ingestion
- Built a headless application architecture on Cloud Run, Firestore, and Cloud Run functions
- Created autonomous coaching agents with Gemini Enterprise Agent Platform and Agent Development Kit (ADK)
- Implemented RAG with Agent Search grounded in scientific research and physiotherapist knowledge
- Used Antigravity to automate software development loops
- Saved 140+ engineering hours in 25 days
- Activated customized routines dynamically
- Reduced software footprint by 20%
- Expected roughly 25% lower running costs over the next year
Architecture
A unified Google Cloud architecture combining BigQuery, Cloud SQL, Cloud Run, Firestore, and Cloud Run functions, with Gemini Enterprise Agent Platform and ADK for coaching agents, Agent Search for RAG grounding, and Antigravity to streamline development loops.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jul 1, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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