Who We Are
Coderica is an AI-first company focused on helping organizations adopt, deploy, and benefit from AI across their entire IT estate. We work from software delivery through mission-critical infrastructure, so teams can move faster without compromising reliability, governance, or operational control.
Our view is straightforward: AI-assisted development only works at scale when it is process-first. Raw code generation is not enough. You need orchestration across roles, auditable decisions from requirement to merge, and a repeatable operating model that engineering, security, and leadership can all trust.
hashd is our flagship product and the practical expression of this vision. It coordinates human and agent workflows into one disciplined system, giving teams the speed of AI with the traceability, accountability, and execution rigor required for serious production environments.
Transparency
RAG / Knowledge Base
planned (SQLite + embeddings), not implemented (planned — see Roadmap below)
Per-project prompt overrides
architecture exists, UI not shipped (planned — see Roadmap below)
Hot-reload config mid-flow
requires restarting the workstream (planned — see Roadmap below)
TUI conflict resolution viewer
no side-by-side UI yet (planned — see Roadmap below)
Cloud execution
everything runs locally (by design)
Inline IDE completions
not our job, use Cursor/Copilot
Cloud sandboxing
your code runs on your machine, not in our cloud
Repository hosting
we orchestrate, we don't host
Model training
we use existing models, we don't fine-tune
What's Next
Planned capabilities are grouped by execution horizon to make priorities and direction explicit.
RAG Knowledge Base
Per-project SQLite with BM25 + vector search.
Per-project prompt customization
Override any of the 21 prompt templates.
Hot config reload
Change autonomy mode mid-flow.
Expanded agent ecosystem
Grok, DeepSeek, local Llama.
Distributed Agent System
Multi-machine coordination.
TUI conflict resolution
Visual side-by-side diff viewer.
CI/CD integration
Run hashd as part of your pipeline.
Metrics dashboard
Time-to-merge, review cycles, agent performance.
Learning from lineage
Provenance data becomes training signal.
Cross-project knowledge
Patterns from project A inform project B.
Predictive conflict avoidance
Detect risk patterns before merge friction appears.