Beyond knowledge management
Nothing your team builds
or decides ever disappears.
The quiet, persistent layer for engineering teams. Precise context, architectural memory, and a soul-driven engine that ensures nothing is lost.
The problem
Your team's knowledge is scattered.
The engineer who made that decision left six months ago.
The reason for this architecture is in a Slack thread no one can find.
Two engineers just rewrote the same auth module. Neither knew.
The cost of forgetting
Engineering knowledge
is expensive to lose.
Every decision buried in Slack. Every architectural rationale that left with the engineer. Every AI agent forced to rediscover what your team already knew. The numbers show the cost.
lost every week searching
Developers spend over ten hours each week hunting for information instead of writing software.
Stack Overflow Developer Surveysay documentation slows them down
of developers say missing or outdated docs are a major productivity barrier.
Developer productivity researchengineering productivity unlocked
Potential engineering improvement when AI has high-quality organizational context.
McKinseyspend 30+ min/day searching
of professional developers spend more than half an hour every day just finding answers.
Stack Overflow Developer SurveyOynix preserves your organization’s engineering memory—so every AI agent and engineer starts with context, not guesswork, and nothing walks out the door when people leave.
How it works
Index. Remember. Compound.
Engineered to scale with your team's knowledge, from raw capture to living memory.
The graph compounds
Core layers.
One memory.
Index
Knowledge graphEvery repo parsed into a live Neo4j knowledge graph — functions, classes, imports, call chains. AST-level precision, zero LLM cost.
Connect
ConnectorsJira, Slack, Notion, Confluence, GitHub — wired straight to your code. Decisions buried in threads become structured graph nodes.
Reason
Ask the graphAgents query the connected graph, not isolated files. Full blast radius, ownership, and decision history in every answer.
Writeback
Auto writebackEvery agent session writes back automatically. No manual curation — the graph records what was learned, the moment it's learned.
Presence
EDITING_NOWWho's touching which file, right now. EDITING_NOW edges with TTL — overlapping work surfaces before Git ever sees it.
Skills
SKILL.mdTeam decisions become SKILL.md — executable context for Claude Code, Cursor, and Codex. Auto-generated, auto-updated.
Compound
Compounding memoryThe graph gets smarter every single day your team uses it. Day 30 context is unrecognizable from day 1.
Everything connected.
One living graphEvery layer feeds every other — the graph doesn't just grow, it compounds. Day 30 context is unrecognizable from day 1.
Real-time presence
Know who's touching which file. Right now.
No more stepping on each other's code. Oynix tracks every edit in real-time. Conflicts detected before Git ever sees them.
Real-time EDITING_NOW presence layer with 15-min TTL
Semantic conflict detection — not line diffs, meaning diffs
Historical resolution memory from your graph
Live now
Programmable intelligence
Your conventions become
AI-executable skills. Automatically.
Generated from team decisions. Updated when decisions change. Compatible with every major AI coding agent.
Intelligent resolution
Two engineers. Same file.
Oynix catches it before Git does.
Overlap in "auth/handler.go"
Sara's changes overlap with John's rate-limiting implementation. Both modified handleLogin(). Semantic merge recommended.
Historical context
Last time this happened (Nov 12): team chose to split rate limiting into middleware. Resolution took 4 minutes.
Nothing is lost.
We're in private beta, onboarding teams one by one. Secure your place — we'll reach out when your spot is ready.
Limited slots released weekly · No spam ever