SessionFS captures AI coding work across tools, turns it into portable sessions, and lets teams resume, hand off, audit, and coordinate that work. Personas, tickets, and AgentRuns reduce custom orchestration while the knowledge base grows from every captured session.
Easy handoffs from humans to agents. Same sessions, same tickets, same knowledge, same system.
AI coding agents are already on your network. The question is whether you can see what they do.
of engineering teams run AI agents without full security approval
have visibility into AI agent communications
more per incident when shadow AI is involved
Sources: Gravitee 2026, Microsoft Data Security Index 2026
Every agent run starts as a captured, portable session your team can inspect, resume, or hand off. Personas claim tickets. AgentRuns enforce CI policy. The orchestration layer your team would otherwise build in-house — portable across 10 local tools and cloud-agent-ready for AWS Bedrock, Google Vertex, and custom API clients via integration docs.
| ID | Tool | Msgs | |
|---|---|---|---|
| ses_a1b2 | claude-code | 47 | Debug auth middleware |
| ses_c3d4 | codex | 31 | Refactor database schema |
| ses_e5f6 | gemini | 23 | Add rate limiting |
| ses_g7h8 | cursor | 52 | Implement OAuth2 flow |
| ses_i9j0 | amp | 18 | Write migration script |
Memory is not a loose summary. It is derived from captured sessions with transcripts, file changes, commands, git state, and provenance. Every session distils into knowledge claims your agents read — and write back to. Architecture decisions, debugging patterns, API contracts, environment quirks. Your codebase documents itself.
LLM Judge cross-references every AI claim against actual tool output and feeds verified findings into the same knowledge base. Trust scores surface in GitHub PR and GitLab MR threads.
Ask that memory directly. The session helper answers questions like “what did we decide about Redis and why?” from the sessions and project knowledge each person can already read, cites the sessions it used, and runs on your own model key, never one SessionFS supplies. It can also propose cleanup — moving stale sessions to Trash, switching Auto Narrative — that only happens when you press Confirm.
DLP scans every session archive server-side — 14 PHI patterns + 20 secret patterns, with BLOCK / REDACT / WARN modes set per organisation. Every captured manifest carries instruction provenance, persona, ticket, and the AgentRun that signed off. Audit-ready by construction.
HIPAA-ready managed or self-hosted deployment. Helm chart hardened with non-root UID 10001, read-only rootfs, RuntimeDefault seccomp. Deployed at a major healthcare system on AWS EKS.
Same tickets, same knowledge, same system — whether the operator is an engineer or an AI agent. The transition happens one persona at a time.
Every engineer assumes a persona (atlas, sentinel, scribe…) on their tickets. Sessions inherit the persona's rules, context, and identity. Define a persona once for the organization and every project in it can use it. Captured work flows back into the knowledge base.
Where most teams start. No AI autonomy yet — just consistent rules and a growing audit trail.
Trusted personas run autonomously on routine tickets — security review, dependency bumps, doc sync — under human supervision. AgentRuns enforce CI policy; LLM Judge flags contradictions before they merge.
Hybrid operation. The persona does the work; the engineer reviews the AgentRun like a pull request.
Whole categories of routine work move to autonomous personas. Humans handle exceptions, novel problems, and the work that requires judgement. The audit trail is the same regardless of which side of the line did the work.
The endgame. Custom orchestration was never built — the same tickets and knowledge base carry the workload through every phase.
Session data never touches shared infrastructure. Choose how you deploy — we isolate the data either way.
We operate it. Your data stays yours.
Dedicated database and storage bucket — no shared infra. We handle updates, monitoring, scaling, and support. Zero DevOps on your side.
You operate it. We support it.
Helm chart deploys to AWS EKS, GCP GKE, Azure AKS, or on-prem. Full network isolation. Bring your own PostgreSQL and object store.
Both options include dedicated support, custom SLA, and 14-day trial license.
Designed for regulated industries and security-conscious teams. SessionFS self-hosted gives you complete control over access, storage, and audit trails.
Ask about compliance requirements →"A major healthcare organization deploys SessionFS on AWS EKS with full network isolation for HIPAA compliance."
— Enterprise deployed, HIPAA environment
Self-hosted deployment, compliance requirements, custom SLA, and pricing for large teams.
14-day trial license available for self-hosted evaluation.
We typically respond within one business day.
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