Product
The Agent-Native Operating Layer,
in detail.
SynOS is the substrate your agents run on. Bring your own product, framework, or harness — the layer gives every agent a self-improving Context Brain, compounding skills, agent-native storage, safe build & deploy, access control, and traces, so you ship your product, not the plumbing underneath it. Self-hosted.
Self-improving Context Brain
Streaming ingestion. Smart extraction. Entity resolution. A shared context graph of skills, entities, decisions, and traces. Self-Learning Loop: every agent trace + every human correction feeds back. The brain compounds.
Compounding Skills
Built once, then shared, versioned, and forked across the team. Installable from a skill marketplace.
Agent-Native Storage
An SoR built for how agents write. Different patterns, controls, and checks than typical DBs.
Safe Build & Deploy
Scanned sandboxes for agents and apps. Shadow → approved → autonomous, within bounded scopes.
Access Control & Audit
Per-skill, per-agent, per-team scopes. Revocable, auditable. Templates, not tickets.
Traces & Self-Learning Loop
Every skill run, every tool call captured. Cost, latency, success, hallucination signal — fed back into the brain.
The Anchor Piece
The Living Context Brain.
A continuously curated knowledge layer every agent in your company can read from. It remembers what your team knows, what your agents have done, and how decisions get made — across every system.
What the Brain remembers
Skill
Learned procedures
How to do a recurring task. Promoted from runs the team approved.
Knowledge
Curated facts
Policies, definitions, business rules. The things your team would put in a wiki — if anyone kept the wiki current.
Entity
Resolved identities
"Customer #4892" in Salesforce = @priya in Slack = priya@acme.com in your warehouse. One graph.
Trace · the source
Raw run history
Every agent run + every human correction. The substrate the other three are distilled from.
Trace is the source. Skill, Knowledge, and Entity are what gets promoted from it.
How the Brain compounds — the Self-Learning Loop.
Every agent run and every human correction lands in Storage as a trace. Curator agents read both kinds — the agent's work and the agent↔human interaction — and surface your company's tribal knowledge: the rules, exceptions, and judgment calls nobody bothers to write down. That tribal knowledge clears a quality gate and promotes into the Context Brain. The next agent run pulls the upgraded Brain. The loop tightens with every interaction.
Continuous curation jobs re-resolve stale entities and prune dead links so the graph stays current.
Sibling Piece · Skills
How Compounding Skills spread.
A skill is a learned procedure — built once, then it belongs to the team. Skills are shared, versioned, and forked the way code is, and installable from a skill marketplace so a working agent capability spreads instead of being rebuilt per project.
Each skill carries its tool list, parameter contract, and scope declared up front — so it rides your access control wherever it runs. Promote a strong run into a skill, share it, and every agent that installs it inherits the upgrade. Skills compound the same way the Brain does.
Sibling Piece · Storage
How Agent-Native Storage works.
Today's harnesses need a shared place to track the work they do. Agent writes are multi-version, partial, contended, revisable — the patterns a typical SQL or NoSQL store wasn't built for. SynOS ships a System of Record designed for how agents actually write, revise, and reference each other's outputs.
It holds decision traces, work product, multi-agent versioning, structured artefacts, and deterministic references the next agent run can pull. Run analytics (Traces, below) sit on top of Storage; the traces here feed the Brain's compounding loop above.
Sibling Piece · Build & Deploy
How Safe Build & Deploy gates execution.
Engineering blocks "let an LLM touch prod" — for good reason. SynOS gives every agent and every app its own scanned sandbox. Build-time scanning catches unsafe imports and secrets before anything runs; egress is policy-controlled per sandbox; per-run identity tokens scope what the running code can touch.
| Mode | What Happens | When to Use |
|---|---|---|
| Supervised | Plans actions, doesn't execute. See what it would do before anything happens. | First days — validate accuracy and judgment |
| Shadow | Reads execute. Writes are logged but don't fire. Build confidence without risk. | Building confidence — verify write behavior is correct |
| Approved | Writes fire only on explicit human approval. Per-action review queue. | Production-grade tasks where mistakes are costly |
| Autonomous | Full execution with per-tool permissions and audit trail. You review exceptions. | When accuracy is proven — trust earned, not assumed |
Sibling Piece · Access
How Access Control & Audit scope skills.
Per-skill, per-agent, per-team scopes. Revocable. Auditable. Templates, not tickets — your AI team defines a scope once and it applies to every agent that installs the skill.
A skill ships with its tool list, its parameter contract, and its role check declared up front. Install once. Share across the team. Permissions ride with the skill, not the user who happens to run it.
Sibling Piece · Traces
What Traces & the Self-Learning Loop capture.
Every run, every tool call. Cost, latency, success and failure, hallucination signal, who-ran-what. Cached and budgeted — predictable cost per decision at scale.
Three consumers: your AI team reads them for analytics; the Brain reads them for the Self-Learning Loop; Permissions reads them to adjust scopes as patterns shift.
Retrieval
Two ways the Brain serves agents.
Some questions have a known shape — pull the right slice and hand it over. Others need a walk through the graph. The Brain ships both.
Pack assembly.
Single call. For questions with a known shape — predictable cost, predictable latency.
Sub-agent walk.
For open-ended questions where the right slice isn't known up front. A retrieval sub-agent plans, calls, observes, and refines as it traverses the graph.
Both paths hand the calling agent the same context envelope — authority-ranked, freshness-aware, policy-redacted.
What's Different
Why existing solutions don't solve this.
Every team we talk to has tried some combination of these categories. Here's what they found missing.
The question to ask any tool: does your agent get smarter after the 100th task? With SynOS, it does.
Bring Your Own Agent
SynOS is the operating layer, not the body.
Engineering teams spend significant time rebuilding context, skills, storage, sandboxes, access control, and trace plumbing for every new agent. SynOS ships all six pieces, pre-built. The brain at the centre comes with compounding skills, storage, safe build & deploy, access control, and traces around it. Three ways to plug in:
Build on SynOS
Building an AI product, platform, or agency offering?
Build it on SynOS. Your agents get a self-improving Context Brain, agent-native storage, sandboxes, access control, and traces out of the box — so you ship the product, not the infrastructure under every agent. Own the brain, skills, and deploy. Bring your own harness and models. Self-hosted in your cloud, or your client's.
Lifecycle
Connect. Profile. Link. Permission. Execute. Trace. Compound.
Only context is extracted — not raw data. Your systems of record remain untouched. Each step exercises a piece of the layer.
Connect
Plug in your data sources. No migration.
Profile
Auto-extract schema, stats, business semantics.
Link
Discover cross-system relationships. Resolve entities.
Permission
Scope tools per skill, per agent, per team.
Execute
Agents run in scanned sandboxes. Reads and writes audited.
Trace
Every run captured — cost, outcome, signal.
Compound
Traces and corrections promote into the Brain. Next run pulls more.
Tools & Actions
Tools with guardrails. Agents that act, not just answer.
Structured, permission-controlled operations that connect agents to your systems. Granular per-tool, per-agent permissions — allow reads on one system while denying writes on another. Every action audited.
Read
Query your CRM, data warehouse, databases, and documents.
Write
Update spreadsheets, create CRM records, insert database rows, send messages.
Communicate
Send Slack messages, Google Chat, email. Route alerts to the right people.
Research
Web search, web scraping, API calls. Bring in external context on demand.
Custom Tools — Extend With Your Own Logic
Save tested queries as reusable tools with template variables. No code deployment — define once, assign to any agent. Your saved, validated query runs deterministically. Scoped write tools restrict which objects a tool can modify.
Connectors
Automatic connectors to your apps. With guardrails.
Standard integration methods — OAuth, API keys, and connection strings. Internal application data can also be integrated through REST API endpoints.
Documents
Google Docs, Notion, Confluence
Data Stores
BigQuery, Snowflake, Redshift, PostgreSQL, MySQL, MongoDB, Google Sheets
Project Management
Linear, Jira, Asana
Communication
Slack, Microsoft Teams, Google Chat, Email (Gmail, Outlook)
CRM
Salesforce, HubSpot
Cloud Infrastructure
AWS (Cost Explorer, CloudWatch), GCP (Billing, Monitoring), Azure
Billing & Finance
Stripe, Chargebee, NetSuite
Code & Deploys
GitHub, GitLab
APIs & Internal Systems
REST API endpoints, webhooks — any system with an API becomes a connector
Need a connector we don't have? New connectors ship fast based on design partner needs.
Triggers
Multiple ways to start an agent.
All triggers feed into the same execution engine with the same graduated trust controls.
Manual
One-click from the UI
Scheduled
Cron-based with timezone
Webhook
External system triggers via POST
Chat
Slack, Google Chat, or built-in UI
Voice
Phone calls, multi-language
Security & Deployment
Enterprise-grade. Self-hosted by default.
Self-Hosted
Single VM in your cloud. Your data stays on your infrastructure. Zero egress.
Managed by SynOS
Dedicated instance provisioned and managed by us. Same architecture, zero ops burden.
SaaS
Hosted multi-tenant for teams that prefer fully managed infrastructure.
All deployment modes use identical architecture — zero code changes to switch between them.
SynOS gives them your company's Agent-Native Operating Layer.
See it with your data.
Walk through the architecture with your actual stack, your actual connectors, and your actual workflows. No slides.
Or read the thesis → on Substack.