Of developers concerned about AI security implications, Snyk Research
90%
Of users abandon AI for mission-critical work due to lack of memory (MIT NANDA, 2025)
Every developer knows this pain:
Explaining the same codebase context 50 times a day
Your AI forgets everything between sessions
Zero visibility into AI costs across your team
How much are you really spending on Cursor/Copilot?
Locked into IDEs you hate
Love XCode but need AI? Tough luck.
Meet AgentSmithy
AI That Knows Your Codebase
Built for Professional Development Teams
Multi-Repository Intelligence
AI understands connections between your repositories
Stop explaining how your microservices communicate – AI knows your architecture patterns
On-Premise Deployment
Keep sensitive code within your infrastructure
Deploy open‑source models locally when compliance requires it – even if performance differs
Centralized LLM Control
Finally see what AI actually costs your team
Manage all AI models, subscriptions, and credits from one dashboard
More features:
AgentSmithy's central server maintains a comprehensive map of your entire codebase ecosystem. It understands how your 100+ repositories connect, which microservices communicate with each other, and what protocols they use. When you're coding in one service, the AI automatically knows about related services and can suggest the correct integration patterns without you explaining the architecture.
Define your coding standards, naming conventions, and architectural rules once in the central dashboard. Every local agent across your team automatically enforces these rules. Whether a developer is working in React, Go, or Python, the AI ensures consistent code style, proper error handling patterns, and adherence to your security guidelines.
The review agent automatically checks every pull request against your coding standards, architectural principles, and security policies. It catches inconsistencies between frontend and backend, verifies API contracts, and ensures new code follows established patterns. Reviews are contextualized with knowledge of your entire codebase.
Unlike tools that force you into specific editors, AgentSmithy works through lightweight plugins for any IDE. The local dev-server architecture means your iOS team can use XCode, Android developers stay in Android Studio, and backend engineers keep their JetBrains setup - all while sharing the same AI knowledge base.
Connect all your repositories from different platforms into one unified context. AgentSmithy indexes code from GitHub, GitLab, Bitbucket, and even internal Git servers. It understands cross-repository dependencies and can suggest changes that affect multiple repos simultaneously.
When investigating bugs, AgentSmithy connects tickets from Jira or Linear with the actual codebase. It analyzes error logs, traces code paths across microservices, and suggests fixes that consider the entire system architecture.
Monitor which AI models your teams use most, track costs per project or developer, and identify the highest-ROI AI features. See which teams are spending the most on LLM calls and optimize your AI budget with detailed usage breakdowns.
Knowledge learned by one developer's AI agent benefits the entire team. Company-specific solutions become part of your collective AI intelligence.
All code analysis happens on your servers. The central management server runs within your corporate network, and local agents process code locally. Sensitive code never leaves your infrastructure. Supports air-gapped deployments.
