Production agent infrastructure

Production-grade AI agents,
live in weeks.

Sabi designs your multi-agent systems and deploys them on your infrastructure, on the fleet and security layer we already operate. The hard part is built, so you ship in weeks instead of two quarters.

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Runs on-prem, in your VPC, or air-gapped, built for enterprises operating agents under real compliance constraints.

Backed by
Khosla VenturesAccelInitialized
END USERSYOUR VPC · ON-PREMWebSlackTeamsAPIagentagentagentagentagentAI SECURITY GATEWAYALLOWEDCONTAINEDExternal APIs · Tools · LLMs
01 · The runtime

Agent Infrastructure

The production fleet your agents run on: sandboxing, state, lifecycle, and channels, operated as one system instead of stitched together per project.

+
02 · The control plane

AI Security Gateway

Network-layer containment for agent fleets: credentials, policy, and audit enforced on the wire, below the SDK, where a compromised agent can’t reach them.

Trusted by industry leaders

The people shaping the next
decade have seen it run.

Live, hands-on demonstrations, not slideware, with leaders across technology and capital.

Sabi live demo with Bill Gates
Bill GatesMicrosoft / Gates Foundation
Sabi live demo with John Doerr
John DoerrKleiner Perkins
Sabi live demo with Russel Tham
Russel ThamTech leadership
Sabi live demo with John Collison and Vinod Khosla
John Collison & Vinod KhoslaStripe · Khosla Ventures
Backed by
Khosla Ventures
Accel
Initialized
Kevin Weil
Advised by
DeepMindDeepMind
AppleApple
MetaMeta
NeuralinkNeuralink
Stability AI
EleutherAIEleutherAI
April 2026

Out of stealth.

Covered in WIRED, Decoder, and the New York Post. 5.7M views on the launch post.

2026

Two rounds, both led by Khosla Ventures.

With Accel, Initialized, and Kevin Weil. Scout checks from Greylock, a16z, Sequoia, General Catalyst, and Kleiner Perkins.

Research lineage

World’s first BCI + agentic AI lab.

A 70K-sensor neural wearable, and the largest non-invasive neural dataset on record.

Team

Built by people who have solved this before.

From Carnegie Mellon ML, Stanford and MIT AI labs, Meta, Magnus Medical, Ray-Ban Meta, Motiv, GoPro, Amazfit, and Kraft Heinz.

The production gap

Shipping an agent is easy.
Running a fleet isn’t.

Intelligence isn’t the bottleneck. Frontier models are good enough. The runtime is: months of fleet plumbing between a working demo and a system in production. Five problems every team hits at scale.

80% ship an agent.
31% reach production.

Isolation

Per-tenant sandboxes and credential boundaries. In regulated industries, not a feature but a legal requirement.

Persistence

Memory that survives sessions, restarts, and infra changes. Most agents forget, or remember wrong.

Scale

Lifecycle for thousands of environments: provisioning, idle teardown, state backup, and restore on any machine.

Channel fragmentation

Web, Slack, Teams, API. Each speaks differently. One agent, three integrations to build and maintain.

Cost economics

Per-token billing breaks at fleet scale. The right architecture runs 4–10× cheaper at the same quality.

The platform

The fleet runtime for production agents.

You choose the agent; we run everything beneath it: sandboxing, state, lifecycle, channels, and SDK plumbing. It’s the same layer our engineers use to put custom agents into production inside enterprises, fast.

Key capabilities

  • Sandbox fleet: provision, pause, resume, tear down
  • Session continuity across restarts and infra changes
  • Multi-tenant state: shared and per-user memory
  • Channel adapters: Web, Slack, Teams, API
  • SDK-agnostic: Claude, OpenAI, OpenCode, or your own
  • Security gateway enforced by default

Scope

We map agentic opportunities across your business units and rank them by impact, feasibility, and risk, before anyone writes code.

Build

Our engineers embed with your team to build the system (tool-use, evals, and guardrails) in your codebase.

Deploy

Live in your VPC or on-prem on open-source models. Variable API spend becomes fixed, owned capacity. No egress, no lock-in.

In your boundary

Every deployment runs inside your network. No customer data crosses the line, by design.

Open models, tuned

Open-source LLMs fine-tuned on your data: accuracy you own, sovereignty by construction.

~20× lower cost

Run-rate a fraction of the commercial API path, at the same quality bar.

AI Security Gateway

Secure the walls,
not just the front door.

Compute isolation isn’t credential isolation. An agent’s keys live in the same sandbox the agent runs in. One prompt injection and they’re gone. Sabi moves them out: secrets stay in a vault and are injected on the wire, below the SDK, where a compromised agent has no path to them.

Credentials

No secrets in the sandbox. Keys live in a vault and are injected per request, on the wire.

Network

Every outbound connection routes through the gateway. There is no path around it.

Audit

A tamper-resistant record of every call, ready for SOC 2 and HIPAA review.

Policy

Allow/deny lists, per-API rate limits, and PII detection, enforced at the wire.

Providers

Runs in front of E2B, Modal, Docker, or Kubernetes. Provider-independent.

MULTI-AGENT RESOLUTION AGENT SWARM Incoming case TriageReconcilePolicyExecute Security gateway Resolved A swarm of specialists, one resolved case. Secured by the gateway, every action logged.
In production today

World’s largest retailer 18h → 30m

A multi-agent swarm for the hard tail of customer issues: triage, reconcile order, vendor, and delivery data, apply refund policy within guardrails, then execute and close. Built in their AWS VPC on open-source models.

73% fewer human handoffs$11.40 → $3 per resolutionLive in 9 weeks

Big-5 media group 8h → 12m

Autonomous paid-media operations across thousands of client accounts: bidding, audiences, creative, anomaly detection, and weekly reporting. Five specialist agents per account, each isolated, every action logged.

64% of account hours freed+22% ROAS in pilotPer-client isolation
Cost benchmark

Open models on your infra vs.
the commercial API path.

Indexed run-rate cost per million tokens on an equivalent reasoning task, measured across 2026 deployments. Same agent, same quality bar. An order of magnitude apart on cost.

Download the benchmark (PDF) ↓ One-page brief · methodology and full figures
Working Session

Start with a working session.

You’ll meet the engineers who’d actually build it. In 60 minutes we scope your highest-ROI use case and walk a live reference architecture, on your stack, with your constraints.

20×
Lower run-rate cost
7–8 wks
Avg. time to production
0
Customer data leaves your network
Book a session →
No sales pitch. You meet the engineers who would build it.