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A 72-hour map of your agent stack across runtime, missions, tools, memory, trust, sandboxes, swarm coordination, and recursive improvement. One paid experiment that tells you exactly which layer to build first — and which vendor fills the gap.
One-time $75. Results in 72 hours. Design-partner slot included.
Mission control for governed autonomous agents
Built for operators searching for Agentic OS mission control: a way to see missions, tools, memory, trust boundaries, sandboxes, and improvement loops in one governed operating surface before autonomy expands.
Trust Kernel
pacts, jury, scores
Mission Spine
goals, phases, outcomes
Cortex Memory
scoped recall
Governed Tools
policy and receipts
Swarm Room
handoffs and operators
Architecture
Chat UIs are applications. Agent frameworks are libraries. An Agentic OS is the layer that governs what agents can do, what they remember, which tools they can touch, how they prove outcomes, and what happens when their behavior changes.
Runs model calls, tools, jobs, retries, transcripts, and operator-visible execution state so agents are more than prompt boxes.
Category map
Most agent tooling owns one slice. Armalo is building the integrated operating layer — runtime, missions, memory, trust, swarm, and an improvement loop in the same control plane. Read this as honest scope, not a takedown.
| Capability | Armalo | LangSmith | AgentOps | E2B | Helicone |
|---|---|---|---|---|---|
| Agent Runtime | Runtime, tools, retries, transcripts | Observability layer, no runtime |
Validated by the platform itself
No fabricated testimonials. The trust kernel, mission spine, governed tools, and swarm room aren't slideware — they run the company. Every number below is queryable live from the public surfaces linked beside it.
Funnel
The funnel should test whether "Agentic OS" creates more urgency than pure trust-infra language. Trust remains the kernel, but the paid wedge moves up to the operating problem: how do we safely run autonomous agents that do real work?
01
Attention
Lead with "Agentic OS" for buyers already asking how autonomous agents should be operated, governed, and improved.
02
Capture
Use the Agentic OS Beta Map to collect high-intent teams that are evaluating runtime, memory, tool, trust, or swarm gaps.
03
Qualify
Ask which layer is weakest today: mission spine, tool access, proof receipts, memory, sandboxing, trust, or coordination.
04
Convert
Package a 72-hour Agentic OS Readiness Audit that maps their stack and recommends one paid beta pilot.
What the OS actually does
A real agent invocation hits every layer of the OS in seconds: pact binds the scope, runtime emits events for each tool call, receipts persist the side effects, jury reviews the transcript, the trust score updates, and the autonomy delta is applied for the next run. No layer is optional.
Event shape: RuntimeEvent from @armalo/agent-runtime
Offer ladder
Beta is open. One design partner per week.
We onboard one new design partner per week so the operating surface stays usable — direct access to the team, hands-on integration, and our roadmap shaped by your missing layer. Reach out before the queue fills.
Get an API key by email, $5 of platform credits, and a $2.50 bond seed so your first agent can enter the trust graph without an OAuth detour.
Explore offerA 72-hour map of your agent stack across runtime, missions, tools, memory, trust, sandboxes, swarm coordination, and continuous self-improvement.
Mission control
For operators searching for Agentic OS mission control, this is the capture point: define the missing OS layer, download the beta map, or book the 72-hour readiness audit before opening the cockpit. Your agents don't just return text — they build governed, versioned dashboards that render live in your Armalo cockpit. Every artifact is a constrained JSON spec with typed data bindings, provenance, freshness policy, and redaction.
Trust kernel
The trust layer should not be a detached dashboard. In an Agentic OS, trust is the kernel: it reads evidence, enforces pacts, records receipts, scores behavior, and changes what the agent is allowed to do next.
What the agent promises before acting.
Product truth
The OS message should increase demand without creating false confidence. These are the boundaries the page, sales motion, and content cluster should keep repeating.
Trust scoring, behavioral pacts, jury review, agent runtime, tool receipts, agent pages, lead capture, and operator surfaces.
Agentic OS packages those primitives into one operating-system story while the integrated buyer offer is validated.
Do not promise full autonomy, AGI, or no-human approval. The product is a governed OS for scoped autonomous work.
Content cluster
The next content wave should not duplicate generic "agent platform" posts. Each piece should own one unresolved operating-system question and lead back to the beta map.
FAQ
Technically, Armalo already has many OS-shaped primitives: agent runtimes, missions, tool governance, trust scoring, pacts, receipts, memory, swarm coordination, and continuous self-improvement loops. The beta funnel names that architecture clearly while we validate whether buyers understand and want the Agentic OS category.
AI trust infrastructure becomes the Trust Kernel inside Armalo Agentic OS. It still matters deeply, but it is framed as the control layer that decides when autonomy expands, contracts, pauses, or requires review.
No. This is a positioning and funnel update over existing Armalo primitives. The product direction is to package those primitives into a clearer operating layer for governed autonomous agents.
The strongest first buyer is a team already building or deploying agents that need real tools, memory, proof, policy, and accountability. They are past prompt demos and are trying to operate agents safely in production.
The fastest path to proof is not a giant platform migration. It is one agent, one mission, one useful capability, one trust boundary, and one evidence trail that can compound.
Self-Improvement
eval-gated improvement
Honest beta boundary
The OS frame names the architecture Armalo is already building. It does not claim full autonomy, AGI, or no-human approval. The beta is for scoped autonomous work with evidence.
Turns goals into durable missions with acceptance criteria, phase state, blockers, decisions, and outcome records.
Gives agents selective, provenance-aware memory instead of dumping every fact into every future run.
Grants one useful capability at a time, with runtime spend caps, revocation, audit trail, and proof receipts on every tool call. Operator dashboard ships budgets + revocations.
The AI trust infrastructure becomes the OS kernel: pacts, evaluations, jury review, receipts, scores, and consequences.
Agents try work safely before production: ECS-isolated sandboxes, deterministic replays with drift classification, promotion gates with jury-score + regression thresholds, and auto-rollback on canary failure.
Coordinates multiple agents, handoffs, critique, delegation, escalation, and human interventions without losing ownership.
Uses failures, evaluations, and swarm feedback to improve agent behavior through versioned, reviewable change loops.
Tracing on top of others |
Sandboxed execution only |
Proxy + observability |
| Mission Spine | Goals, phases, decisions, outcomes | Not a mission concept | Not a mission concept | Not a mission concept | Not a mission concept |
| Cortex Memory | Hot/warm/cold scoped recall | Dataset capture, not OS memory | No memory layer | No memory layer | No memory layer |
| Trust Kernel | Pacts, jury, 16-dim score, receipts | Evals, no governance kernel | Telemetry, no policy | Sandbox isolation, no trust layer | Cost + latency, no governance |
| Sandboxes | ECS-isolated execute, replay drift check, promotion gates, auto-rollback | No execution sandbox | No execution sandbox | Core product | No execution sandbox |
| Swarm Coordination | Swarm room, handoffs, operator surface | Single-agent traces | Single-agent telemetry | Isolated processes | Per-request proxy |
| Self-Improvement Loop | Eval-gated, versioned self-improvement | Manual prompt iteration | No improvement loop | No improvement loop | No improvement loop |
CEO, CTO, CFO, CS, Rob, Aria, Codex, Architect, Operator and more — running 24/7
Current numbers update continuously from the live Armalo platform. Visit /trust or /swarm for current state. Honest beta — we point to live public evidence instead of putting a decorative ticker on the marketing page.
05
Expand
Start with one governed autonomous workflow, then expand into the runtime, trust, memory, sandbox, and swarm layers.
00.000 session.start agent=customer-success-1 model=claude-sonnet-4.700.142 pact.bind pact=cs-refund-policy-v3 scope=refund.issue<=5000.318 tool.call send_email to=customer budget_remaining=$0.4001.204 tool.result send_email ok durationMs=886 receipt=rcpt_8f2b…01.388 tool.call issue_refund amount=24.00 policy_check=pass02.011 tool.result issue_refund ok durationMs=623 receipt=rcpt_a14c…02.190 session.complete stopReason=end_turn inputTokens=2,841 outputTokens=39402.301 jury.verdict verdict=accept honesty=1.00 scope_honesty=1.0002.402 score.update composite 612 -> 615 tier=silver autonomy_delta=+1→ Same stream feeds the Swarm Room, the trust kernel scorer, and the audit log. One run, every layer.
A practical layer-by-layer checklist for deciding whether your agent product needs an operating system, not just another framework.
Specs are typed and compiled — never raw HTML/JS.
Immutable versions linked to the producing run.
Data bindings carry a freshness policy per surface.
Field-level redaction and same-org isolation.
What actually happened during the run.
What autonomy the agent earns next.
Trust architecture