NewNow works with Openclaw

Your team's self-improving
memory.

Most teams run AI individually, so the work resets every session. Stash turns every run across the team into a shared, evolving asset that every agent builds on.

One-command install

$bash -c "$(curl -fsSL https://raw.githubusercontent.com/Fergana-Labs/stash/main/install.sh)"
MIT licensedSelf-hostable
team · fergana/ sessions
Live
R
rexagentupdatedauth/session_refresh.py
fixed 401 race on concurrent refresh, linked to auth patterns
just now
S
samhumanopenedbackend/gateway/
reviewing rate-limit bump from the rex debug session
2m
S
scoutagentqueriedstash search
“why was the rate limit raised to 500?” · 8 sources
4m
N
novaagentupdatedfiles · memory-leak-v2
4 pages organized, 12 session sources attached
9m
A
arihumancommentedfiles/api-gateway
keeping this open; will re-use the worker-pool pattern next week
22m
streaming · 412 events / hr4 agents · 3 humans
Works with
Claude CodeClaude CodeCursorCursorCodexCodexOpenCodeOpenCodeOpenclawOpenclaw

Install

One command.

Automatic setup. No yaml, no manual plugin wiring. The CLI detects your agents and wires them up for you.

Use our managed service and be streaming in a minute, or self-host on your own infra if you'd rather keep every session in your own Postgres.

install.sh
$bash -c "$(curl -fsSL https://raw.githubusercontent.com/Fergana-Labs/stash/main/install.sh)"
» installing stash cli
» scope ✓ team/fergana
» sign-in ✓ sam@fergana.dev
» workspace ✓ backend-api
» plugin claude-code · cursor · codex
✓ ready. your team's memory is streaming.
$

Why teams plateau on AI

Individual AI usage doesn't compound.

Every engineer is running Claude, Cursor, or Codex on the same repo. The insights, fixes, and gotchas from each session evaporate the moment the window closes. Next week, someone re-asks what was already answered.

Stash captures every run across the team and turns it into a shared layer your agents can query. The second time a question comes up, an agent answers it from the team's own sessions instead of starting from scratch. Call it a hive mind for your agents.

Questions your agent can now ask, and answer

01“Why did Sam bump the rate limit from 100 to 500?”rex · agent
02“Has anyone already tried fixing the memory leak in auth?”scout · agent
03“Is anyone else currently working on the API gateway?”nova · agent
04“What pattern did we land on for background workers last sprint?”rex · agent

How it works

Sessions. Files. Search.
The asset builds itself.

01Stream
14:02tool_callread_file(auth.py)
14:02editsession_refresh.py
14:03reviewpr/#482
14:04testpytest auth/

Every session flows into a shared store.

Prompts, tool calls, and session summaries push to your workspace’s Sessions as they happen. Nothing to remember to save.

02Files
auth-patternsroot
session-refresh 401 race
rate-limits · 500/min
memory-leak-v2new

Teams shape durable pages.

Pages, uploads, and folders stay in Files. Sessions remain searchable sessions, and useful outputs can be promoted into durable pages.

03Search
/stashwhy was the rate-limit raised?
sessions/rex:14:0262%
files/auth-patterns21%
files/gateway.py11%

Every agent queries the whole team's work.

stash search runs a cross-resource agentic loop over files, sessions, pages, tables, and Stashes. Your agent answers with sources, not hallucinations.

See the memory form

Your team's brain,
actually visible.

Every session, page, and table gets embedded into one space. Stash plots them so you can see how your team's knowledge clusters, and which pages have become hubs the tree leans on.

embedding projectionmemory_reading_store
43 / 1,284 points
Sessions
Files
Tables
auto-rotate

3D embedding projection. Sessions, pages, and tables projected with PCA. Clusters form around topics — not folders.

file treefiles · reading-store
12 pages · 19 Stashes
pgvector-howtoreading-store-archhnsw-vs-ivfflatchunking-strategyrerank-patternsrecall-at-kembedding-modelscost-per-1keval-harnessrelease-notesindex-playbookfilter-push-down
hub
leaf

Files file tree. Nodes are pages, edges are Stashes. Orange nodes are the hubs your agents keep citing.

What's inside

One team's work,
every agent's context.

H

Shared sessions

Every prompt and tool call streams to a team-wide session log. Searchable, filterable, attributable.

eventsper-agentreplay
W

Files

Rich collaborative pages with Stashes, file tree, and pgvector semantic search.

Stashestreesemantic
S

Agentic search

stash search runs a cross-resource loop over every surface in the workspace. One query, every source, with receipts.

cross-sourcecitedstreaming
V

Visualizations

See your team's memory as it forms: embedding projections, file trees, activity timelines, and knowledge-density maps you can actually look at.

embeddingstreetimeline
R

Stashes

Publish sessions, pages, and files together as a polished link anyone can inspect.

publishsessionsfiles
P

HTML pages

Store agent-made reports, dashboards, and documents as first-class pages.

htmlreportsdashboards

Compound your team's
AI work.

Your team is already running agents. Stash turns those runs into a shared advantage that grows every day.

MIT · Self-hostable