Runtime for free agents
Your agent gets a shell.
You keep the keys.
Real OS. Real shell. Real tools — every CLI your engineers use. The boundary outside hides credentials, gates the network, records every move. The agent never knows it's there.
Most agents are LLMs in a function-call cage.
Every agent platform you've seen works the same way. The model can only call functions your team hand-wrapped for it. Want a new capability? Wrap a new function. No matter how clever the model gets, those wrappers are the ceiling.
On Evershell, the agent gets a real computer — bash, curl, jq, apt, pip, git, every CLI your engineers use, three decades of unix tooling, an entire ecosystem. It composes its own commands, installs a library it just read about, greps its own log to find what broke, and picks up where it left off yesterday. The agent works the way your engineers work.
Agent platforms today
- A JSON-schema menu of pre-wrapped tool calls
- Every new capability is engineering work
- Can't install a library the model heard about yesterday
- Can't grep its own log to debug a failure
- Can't compose
curl | jq | awk - Three decades of unix tooling, off-limits
- Stateless — every run starts blank; memory is a service you bolt on
- Locked to one vendor's tool schema
An LLM behind twelve fixed buttons.
Agents on Evershell
- Real OS — full bash, full apt/pip, every CLI you'd put on a laptop
- Composes tools — pipes, scripts, loops, multi-step workflows
- Installs what it needs at runtime, no redeploy
- Reads its own errors, retries, adapts
- Three decades of unix tooling, free
- The productivity boost an engineer gets from the shell
- Keeps state across runs — its filesystem is its memory
- Any model, any framework — swap the best one in anytime
An engineer that happens to be an LLM.
Hire your agent like an engineer.
Manage it like an employee.
Day one looks like any new hire's — a workstation it comes back to, scoped reach, an audit log of what mattered.
A new CVE alert arrives. The agent reads it, pulls the asset list and deps, and reports — are we affected, where, how bad. Hour-long manual check, done in seconds. Give it a playbook and it drafts the patch ticket, pages on-call, applies the mitigation. Outbound security updates go through a separate sub-agent with reach to one Slack channel — and nothing else.
From answering one question to driving the whole loop — same boundary, same audit, the whole way.
Giving an agent a shell sounds reckless.
It isn't, when the network is the boundary.
The agent runs in its own isolated sandbox with a real operating system. Inside, it looks like a normal computer. Outside, every connection it makes flows through a transparent control layer you operate.
The agent doesn't know it's there. It makes normal HTTP calls to normal APIs. The boundary decides whether the call is allowed, attaches the right credentials, records what happened, and either lets it through or stops it cold. A boundary the agent can't bypass — it runs outside the sandbox, not as a library inside it, no matter which model is driving.
Enforced by infrastructure — not by an SDK in your agent's process
Transparent gateway
Every outbound call passes through a gateway you control. No bypass, no escape, no DNS trick. The agent never knows it's there.
Hidden credentials
Agents never hold API keys. The gateway attaches them only at the moment of the call. If the agent is compromised, your credentials aren't.
Complete audit
Every action recorded: who, where, with what credentials, with what result. Queryable, exportable, complete.
Spending caps
Set request and cost limits per agent and per capability. The gateway enforces them so a runaway agent can't run away.
Per-task identity
Every task gets its own short-lived cryptographic identity. Every action is attributable to a specific agent, role, and run.
Domain control
Each agent's world is shaped by an allowlist. Anything outside doesn't resolve. Locked down by default.
The console.
Designed for operators. Configure each agent's reach, watch the fleet live, analyze across destinations, drill into a single decision.
01Decide what each agent can reach — before they run.
Define each role's reach — what domains, what methods, what budgets. See the full topology and risk profile in one view, before anything runs.
02See them work — in real time.
Every running agent, every connection they're making, every policy decision — as it happens. No log-tailing, no SDK callbacks, no waiting for an export.
03Understand the fleet — at a glance.
Traffic, denials, token usage, costs — broken down by destination, agent, and workspace. Filter, slice, and export.
04Drill into any action — ever.
Every request is kept with full context: identity, destination, response, latency, cost. The answer to "what did the agent do?" is one query away.
Built on infrastructure your team already trusts
Ready to let your agents off the leash?
Tell us about your stack — we'll find a time to walk through how Evershell fits.
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