Case Study
Kindo
Securing and Scaling Enterprise AI with AWS GenAI
June 2025 | LOCATION
INDUSTRY
AI
Project Type
GenAI Platform Re-Architecture
BaSIS Services
GenAI, Multi-Model Orchestration, AI Security Engineering
Technology Leveraged
Amazon Bedrock, Amazon SageMaker, AWS ECS, AWS Fargate, Amazon RDS, pgvector, AWS S3, AWS Lambda, AWS ElastiCache, Cloudwatch, AWS X-Ray
Kindo
Securing and Scaling Enterprise AI with AWS GenAI
Problem / NEED
Kindo, an enterprise AI security startup, needed to transform its infrastructure to support a multi-agent AI orchestration platform used by major enterprise clients. Their existing environment, based on Railway, suffered from critical availability failures during key client demos, undermining trust with accounts like Station Casino and Farmer’s Insurance.
At the same time, Kindo’s product required dynamic multi-model coordination (OpenAI, Bedrock, Gemini), custom AI agent creation, real-time project integrations (Jira, Zendesk), and strict security protocols including PII masking and RBAC enforcement. Their infrastructure couldn’t meet the demands of real-time processing, advanced AI orchestration, or enterprise reliability, which directly hindered growth and revenue.
Solution
Basis migrated Kindo’s platform to a scalable, secure AWS-native architecture in under a month, eliminating availability issues while expanding capabilities for complex multi-agent AI workflows and enterprise-scale adoption.
Key elements of the solution included:
- Amazon Bedrock: Primary GenAI foundation using Claude 3.x for enterprise-grade reasoning and response generation.
- Multi-model orchestration: Support for OpenAI, Bedrock, and Gemini with dynamic routing and normalization.
- pgVector on Amazon RDS: Vector storage for semantic search and Retrieval-Augmented Generation (RAG) pipelines.
- Amazon ECS with AWS Fargate: Serverless container orchestration for scalable, concurrent agent deployments.
- Amazon S3 & Lambda: Event-driven ingestion and document processing with automatic tiering and notification handling.
- Cerbos & Presidio: Role-based access control and PII masking to meet compliance requirements.
- Amazon ElastiCache: Context caching for fast, stateful multi-turn conversations.
- Amazon CloudWatch & X-Ray: Full observability for availability, agent responsiveness, and SLA compliance.
The platform now supports custom AI agent creation (e.g. project estimator agents, product manager agents) with real-time integrations across Jira, Zendesk, and Linear—driven by a scalable, secure, and high-availability AWS infrastructure.
RESULTS
The AWS migration delivered critical improvements that enabled Kindo to achieve enterprise credibility and rapidly expand adoption:
- Platform availability: Achieved zero downtime during demos and client onboarding post-migration.
- Client acquisition success: Closed and retained major accounts including Station Casino, Aloha Freight, and Farmer’s Insurance.
- Processing speed: Reduced complex project planning workflows from days to seconds with multi-agent coordination.
- Scalability: Supported hundreds of concurrent enterprise users and dozens of custom agents per tenant.
- Enhanced development velocity: Added new product features during the AWS migration without sacrificing reliability.
Kindo now has a production-grade, extensible architecture for secure GenAI operations across multiple clients and verticals, positioning them as leaders in enterprise AI security orchestration.
Technology Leveraged
