Technical knowledge governance

AI agents need more than memory.
They need governed technical knowledge.

SoluCortex keeps your project decisions, risks, conventions and lessons approved, current and traceable, so every Codex, Claude or ChatGPT session starts from reliable context.

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SoluCortex — Project: ConflictCheck · 47 memories
decision We use pgvector instead of Pinecone to keep everything in PostgreSQL imp 9
architecture Per-project API key in Authorization: Bearer header imp 8
risk The embedding model may change - version embeddings by model imp 8
pattern Chained jobs: ProcessMemory → Summary → Embedding imp 7
historical bug Route name conflict between API and web resolved with api.v1 prefix. imp 6
context Stack: Laravel 12 · PHP 8.4 · PostgreSQL 16 · Docker imp 10
Context ready
4.2 KB
For Codex / ChatGPT
Semantic search
"How do we handle authentication?"
→ 3 relevant memories
Approved today
12
+3 new in queue
100%
Context recovered instantly
0
Times you repeat yourself
< 1s
Semantic search across the whole base
The problem

Your team knowledge
evaporates with every session

Every time you open Codex, ChatGPT or a new conversation, you start from scratch. Decisions, risks and conventions get scattered across chats, docs and people instead of staying as usable project knowledge.

😩
Without SoluCortex
The team pastes README files, AGENTS.md notes and architecture docs again and again. New members ask the same questions, bugs repeat and AI agents act without historical context.
🧠
With SoluCortex
Your project knowledge lives in a governed base that stays approved, current and traceable. Codex starts with the right context in seconds, agents save what they learn automatically and the team queries in natural language.
What the platform does

The system that keeps technical knowledge
useful for people and agents

SoluCortex turns scattered notes into approved context that reduces repetition, speeds up onboarding and makes AI assistants safer to use.

🗂️
Knowledge organized by impact
Capture decisions, risks, conventions and lessons with type and importance so the team can find what matters fast and avoid repeating mistakes.
🔍
Semantic search that saves hours
Ask in natural language and surface the exact decision or risk without digging through chats, docs or old threads.
📸
Snapshots for instant handoff
Turn the current state of the project into an AI-ready brief for onboarding, incident response or a new session.
🤖
API for systems and agents
Let tools create, search and approve knowledge directly so context capture happens as part of the workflow.
✅
Human approval before context spreads
Keep risky or low-quality knowledge out of live context until someone validates it.
🔗
Traceable relationships
Connect related decisions, sources and follow-ups so no one loses the why behind a choice.
Two pillars

The two disciplines that redefine
how teams work with AI

SoluCortex was built to make both possible - not as philosophy, but as real infrastructure your team can use today.

🔄
Loop Engineering
The work pattern where each agent session accumulates knowledge instead of starting from zero. In a team with Loop Engineering, the tenth Codex session is ten times smarter than the first because context grows with every work cycle.
SoluCortex closes the loop →

Captures what was learned in each session, indexes it semantically and delivers it ready for the next one.

🏗️
Harness Engineering
The discipline of building the infrastructure that frames and amplifies AI agents with the right context, the necessary constraints and project memory. Without a harness, agents improvise. With a harness, they produce with precision.
SoluCortex is the harness →

A taxonomy of 9 memory types, source approval, lifecycle and intelligent context ranking.

Comparison

Not a replacement for memory tools.
The governance layer above them.

Most tools store, graph or retrieve context. SoluCortex decides what becomes approved knowledge and how AI agents should consume it.

🧭
Graphify
Graph memory infrastructure
Useful if you need graph-centric recall. SoluCortex sits above it to govern what gets approved and delivered to agents.
🧭
Graphiti / Zep
Memory middleware
Good for capturing events and relationships. SoluCortex adds the product layer for approval, lifecycle and team rules.
🧭
Mem0 / Letta
Agent memory layer
Helpful for memory persistence. SoluCortex turns that persistence into trusted, traceable project knowledge.
🧭
Obsidian / Notion / Confluence
Docs and knowledge bases
Great for human documentation. SoluCortex makes the knowledge operational for AI sessions, not just readable for people.
🧭
PostgreSQL / pgvector
Storage and retrieval infrastructure
Solid foundation. SoluCortex is the experience and governance layer that turns raw vectors into usable context.
🧭
SoluCortex
Governed knowledge layer
Sits above storage and memory tools to control capture, approval, retrieval and traceability for AI teams.
The business case

How much is your team
spending on manual context dumps?

Every time someone pastes AGENTS.md, README and technical decisions into Codex or Claude, they waste tokens and time. Calculate the real impact on your team.

⚙️ Team parameters
👥 Team members 5
Developers, QA and tech leads who actively use AI
⚡ AI sessions per person / day 10
An active dev in Claude Code or ChatGPT opens 8-15 sessions per day
📄 Manual context tokens / session 10,000
AGENTS.md (~2K) + README (~2K) + architecture docs (~3K) + decisions + conventions → typical real-world range: 8,000-15,000 tokens
⏱️ Minutes building context / session 6
Search files, copy, paste, verify nothing got cut off - real average: 5-8 min
💵 Developer hourly rate (USD) $35
Actual cost to the company per hour of developer work
💸 What your team loses today
—
per month in team time spent manually pasting context
—
hours / month
—
hrs / person
—
sessions / month
🚀 With SoluCortex you recover
—% reduction
—
per month · dropping from 6 min to ~1 min per context session
📊 Net ROI by SoluCortex plan
Free
$0 / month
—
net savings
—
Starter
$49 / month
—
net savings
—
Pro
$99 / month
—
net savings
—
Business
$299 / month
—
net savings
—
🔢 Tokens / session (relevant if you use the direct API)
Without SoluCortex —
With SoluCortex (semantic snapshot) —
* Assumes 22 work days/month. Net savings = recovered time - plan price. With SoluCortex the context arrives in ~1 min via semantic snapshot (vs 6 min manually). If net ROI is positive, SoluCortex pays for itself and creates real gain for your team.
How it works

From raw notes to governed context

SoluCortex does not require changing your workflow. It fits where you already work and adds approval to the knowledge that should influence AI.

1
Capture
Save a decision, risk or lesson from the UI or API before it disappears into chat history.
2
Classify
Assign type, importance and source so the knowledge is searchable and comparable.
3
Approve
Validate what becomes trusted context and keep the rest out of live use.
4
Use
Agents and humans retrieve approved knowledge through search, snapshots or context builds.
5
Retire
Close outdated memories when a decision changes so context stays current.
Ideal customer profile

Built for teams where bad context is expensive

If your team already uses AI to build software, SoluCortex keeps technical knowledge current, approved and traceable across people, teams and agents.

🎯
Engineering teams using AI daily
Codex, Claude or ChatGPT are already part of delivery, so context quality directly affects output.
🎯
Teams with changing decisions
Architecture, product and platform choices shift often and need a clear historical trail.
🎯
Fast-growing orgs onboarding constantly
New people need to understand the project quickly without relying on one person to explain everything.
🎯
Sensitive or regulated systems
Teams need approved context, traceability and clear control over what AI agents can consume.
🎯
Teams with repeated bugs or rework
When lessons from past incidents are lost, teams repeat the same mistakes. SoluCortex keeps fixes, risks and decisions available for future work.
🎯
Multi-agent or multi-team environments
When multiple teams or AI agents work on the same product, shared knowledge needs approval, traceability and clear governance.
Harness Engineering at scale

Built for
autonomous agents

SoluCortex is the core of your Harness Engineering stack. It exposes a complete REST API so your Codex or Claude agents can store what they learn and retrieve what they need - without human intervention.

Claude / Codex
OpenAI Assistants
n8n / Make
Python SDK
REST · JSON
# Save a new memory POST /api/v1/memories Authorization: Bearer scx_tu_api_key { "type": "decision", "title": "We use pgvector instead of Pinecone", "content": "Decision: keep everything in PG...", "importance": 9 } # Semantic search POST /api/v1/search/semantic { "query": "How do we handle authentication?", "limit": 5 } # Boot context for Codex POST /api/v1/context/build → Returns a snapshot ready to paste
Security

Built with security
from day one

Every component was designed to protect your team knowledge. No compromises.

🔑
API keys with SHA-256 hash
API keys are never stored in plain text. Only the SHA-256 hash is saved. Not even the SoluAI team can read your key after it is created.
🔒
AES-256 encrypted sessions
All user sessions are encrypted with AES-256-CBC. Session tokens are opaque, signed and cannot be forged or reused out of context.
🚦
Rate limiting per API key
Each API key is limited to 120 requests per minute. Abuse or brute force attacks are automatically blocked before they reach the database.
🏗️
Total project isolation
Each API key can only access data from its own project. It is impossible to read memories from another project, even with a valid key from the same team.
🛡️
SSRF protection
External integrations go through a guard that blocks requests to private IP ranges, loopback and cloud metadata endpoints. No exceptions.
🔎
Debug disabled in production
APP_DEBUG is disabled in production. No stack trace, environment variable or internal information is exposed to the browser or API responses.
Clarity

SoluCortex is not for everyone.
And that is good.

A system that tries to do everything ends up doing nothing well. SoluCortex does one thing: keep your team's technical knowledge available to AI.

📋
It is not a project manager
SoluCortex does not manage tasks, sprints or milestones. Use Jira, Linear or Notion for that. SoluCortex stores the <em>knowledge</em> your team generates while working.
💬
It is not a chatbot
There is no built-in conversational AI interface. SoluCortex is an API and a management UI. You bring your LLM (Claude, GPT-4, Gemini) and SoluCortex gives it the context.
💾
It does not store source code
SoluCortex does not index your repository or mirror your code. It stores decisions, patterns and context about the code - not the code itself. Your repo stays in Git.
🤔
It does not make decisions for the team
SoluCortex retrieves and organizes knowledge, it does not reason about it. Technical decisions are still made by your team. The system only ensures context is available when needed.
🎫
It is not a ticket system
There are no issues, comments or complex approval flows. "Approval" in SoluCortex is only the quality gate for what knowledge enters the semantic base.
🚫
It does not access data from other projects
Isolation is absolute. An API key from one project can never see, read or infer data from another project, even if they belong to the same team or instance.
Start today

Your team has been losing
technical context.

SoluCortex is the layer that keeps decisions, risks and conventions approved, current and traceable so every AI session starts from the same source of truth.

Start free →