Repos is a source control product co-optimized with our suite of fast, specialized coding models. It's git compatible, high throughput, and has built-in codebase retrieval.
Intent
I need it when
Quickly integrate AI code generation capabilities into existing engineering pipelines with minimal onboarding
Relace offers a free tier and hosted API that enables experimentation within minutes. Enterprise and self-hosted setups include guided onboarding, and the simple integration model allows teams to start using specialized models immediately without extensive infrastructure changes.
Reduce latency and costs in code generation by replacing frontier LLMs with specialized models
Relace's in-house SLMs are purpose-built for coding workflows and deliver faster inference than general-purpose LLMs while reducing token consumption. Token-based pricing ($0.05–$3.00 per million tokens depending on model) scales with actual usage, lowering costs for high-throughput agent deployments.
Accelerate autonomous code generation and reduce errors in AI-driven development workflows
Relace provides specialized SLMs trained for code generation tasks (apply, search, rank, embed) that outperform general-purpose LLMs on utility tasks. The fast-apply model merges file edits at 10,000 tokens/second and semantic search scales to large codebases in under 2 seconds, enabling reliable autonomous codegen at scale.
Implement fast, accurate code retrieval and merging for CI/CD pipelines and automated PR reviews
Relace Repos provides source control designed for agents with lightweight push/pull operations, no rate limits, and automatic indexing for two-stage retrieval. The fast-apply universal code merging model and best-in-class semantic search enable rapid PR reviews and automated fixes without performance bottlenecks.
Deploy AI coding infrastructure with enterprise security and compliance requirements
Relace is SOC 2 compliant and offers self-hosted, on-premise, and VPC-isolated deployment options where code never leaves the controlled environment. Data is encrypted in transit and at rest, providing teams with full control while maintaining optimized inference performance.
Drop
Not a fit when
User needs general-purpose LLM capabilities unrelated to code generation or source control workflows
Organization requires on-premise deployment without technical infrastructure support for VPC-isolated setups
Team lacks integration capacity for API-based token consumption models and prefers flat-rate subscription pricing
Use case involves non-code document retrieval or merging where specialized coding models provide no advantage
Budget constraints prohibit per-token pricing model with variable costs based on codebase size and agent throughput