COMING SOON · EARLY ACCESS OPEN

The AI agent control plane
and harness.

Spec, scope, build, run, observe, control, and optimize swarms of agents — in one place.

The model is the brain. The harness is the operating system.

Models create capability.
Zahara creates deployability.
// BETTER AGENT PERFORMANCE COMES FROM THE SYSTEM AROUND THE MODEL
// ANTHROPIC

When you evaluate an agent, you are evaluating the harness and the model together. The scaffold is what enables the model to act.

// OPENAI

Tools, orchestration, run loops, and guardrails are required for reliable agent deployment — not just model choice.

// MICROSOFT

Enterprise agents need observability, registry, identity, lifecycle, and a control plane — the infrastructure of operation.

Agents are in production.
Reliability is the bottleneck.

The industry stopped asking "can the model do it" and started asking "can I trust it at scale." That gap — between a demo that works and an agent that ships — is the harness. Zahara is that layer.

MODEL ACCESS
solved
Commodity. Five major labs, open weights, inference at scale.
ORCHESTRATION
fragmented
LangChain, CrewAI, OpenAI SDK, custom scripts — no common runtime.
OBSERVABILITY
missing
Traces exist. Runtime knowledge graphs and hot-path detection do not.
GOVERNANCE
urgent
Audit, policy, rollback, identity — required to cross the enterprise line.

The agent is not just the model.
It's the harness around it.

Every production agent is a model plus a scaffold: tools, memory, guardrails, evals, routing, identity, state. The scaffold is where performance, safety, and reliability actually live. Zahara makes that scaffold a first-class product surface.

// THE HARNESS · ZAHARA MODEL the brain Specagent spec JSON Scopeidentity / brief Buildvibe / flow / pro Runruntime gateway Observegraph · clinic · trace Controlguardrails · HITL · audit Optimizeeval · version · rollback Better agent performance = better harness + stronger evals + tighter control

Four ways to build.
One agent spec.

Chat it into existence, drag it in a flow, write it in code, or import what you already have. Every path produces the same versioned agent spec and inherits the full Zahara runtime — observability, guardrails, routing, audit, all of it.

What do you want to build?

Describe your idea — Zahara drafts a ready-to-run agent spec in seconds.
A support agent that handles billing questions and escalates refund requests
INDUSTRY (optional)
⚡ SaaS / Tech 🛍 E-commerce ✚ Healthcare $ Finance ⚖ Legal ◊ Education ◉ Marketing ◈ HR & Ops
STARTER TEMPLATES
Support Agent
Handle queries with empathy
Research Agent
Synthesise and summarise
Content Agent
Write blogs, copy, social
Sales Assistant
Qualify and handle objections
Workflow Agent
Multi-step orchestration
Data Analyst
Surface insights from data
Retrieval Agent
Knowledge base search
Customer Ops
Onboarding and renewals
Input for quick run... (Enter)
▶ StartTriggerManual ▦ ModelProviderOpenAI ◐ ToolTypeweb_search ◐ ToolTypecode_exec ↓ OutputSinkConsole log
New Agent v1
● active
AGENT FILES⊕ ↑
No files yet.
+ Create a file ↑ Upload a file
⏱ VERSIONS
v1currentSoon: rollback
No file selected✓ Save
{ }
Select a file from the workspace to start editing.
✦ Run OutputView in Clinic →

Import an agent

Paste your content and Zahara auto-detects the format — or choose an adapter below.

SOURCE FORMAT
Zahara SpecFull
Native Zahara agent spec
MCP ManifestFull
MCP tool registry
OpenAI AgentsFull
Assistants or Agents SDK
FlowisePartial
Exported flow JSON
LangGraphPartial
State graph import
Claude Code / SDKPartial
Agent JSON or CLAUDE.md
Show 3 more...

Graph-first agent tracking.
Not another pretty trace.

Realtime, streaming knowledge graph of every agent run. Watch nodes and edges light up as the agent traverses models, tools, services, memory, guardrails, and audit events. Scrub history. Isolate hot paths. Inspect causal clusters. Compare live behavior against past runs and versions.

View controls
Fleet view: all agents
Family view: parent + child
Single agent deep dive
Show only hot paths
Compare vs previous version
Legend
Agent
Run
Tool
Service
Step
Guardrail
Signal
Hypothesis
Streaming event feed
LIVE NODES
148
ACTIVE EDGES
426
TRAVERSAL
84/sec
HOT PATHS
7
BLOCKED
3
CONFIDENCE
0.91
Scope · Fleet / Family / Single · replay 1x 2x 5x streaming
gpt-4o-miniModel planner.stepReasoning step memory.storeState + artifacts web_searchTool run_1842Streaming run All agents · family · single audit.eventRecorded action retrievalService latency spikeSignal validatorStep budget.guardrailGuardrail search timeout cascadeHypothesis · 0.91 output
Selected cluster / family
search timeout
cascade
candidate
root cause
Nodes:
17
Hot edges:
6
Appears in:
71% slow runs
Confidence:
0.91
Avg added latency: +1.8s
Tool retries: 2.7/run
Temporal path history
timenode · change
SUCCESS Run_5534494b run_ab4d1efc5534494b $ 0.000085 ⏱ 634ms # 144 ⟳ Replay · 13/13
$ COST
$0.000085
⏱ LATENCY
634ms
total run
# TOKENS
144
2↑ 142↓
◉ MODEL
gpt-4o-mini
OpenAI
Timeline · Raw13 events

Govern like
infrastructure.

Budget caps, guardrails, tool allowlists, human-in-the-loop gates, policy enforcement. Not bolted on. Built into the runtime from day one. Every violation goes straight to the immutable audit log.

Per-agent budget caps

Daily spend limits enforced at the runtime layer. `budget.blocked` events hit the audit log the moment a cap is crossed. No surprise bills.

Runtime guardrails

Tool allowlists, step caps, duration limits, output validators. Enforced by the backend, not trusted to the prompt.

Human-in-the-loop gates

Tie HITL checkpoints to skill metadata. High-risk tool calls pause for operator approval before they fire.

Kill switch + audit trail

Stop any agent mid-run instantly. Every action, every policy evaluation, every state change is cryptographically anchored to the agent spec version.

Audit feed — immutable log
live

Improve with
evidence, not guesswork.

Evals turn iteration from opinion into measurement. Version control + rollback turn every improvement into a safe commit. Use traces, eval scores, and cost data to make agents better, run after run.

Eval harness
// SUPPORT-ROUTER-PROD · v12 vs v11
Answer accuracy94.2% (+3.1%)
Tool call precision91.6% (+5.4%)
P95 latency3.4s (+0.2s)
Escalation rate6.8% (−2.1%)
Cost per resolution$0.012 (−18%)
v12 wins on 4/5 dimensions · P95 regression flagged · Review required before promote
Version timeline
// PROMOTE · COMPARE · ROLLBACK
v12current · 94.2% accuracy
4/17/2026 · tool allowlist updated · HITL added for refunds
v1191.1% accuracy
4/15/2026 · routing policy tuned
v10rolled back · 87.3% regression
4/12/2026 · new prompt caused escalation spike
v989.4% accuracy
4/08/2026 · memory.store added
v886.1% accuracy
4/03/2026 · baseline
Rollback a bad release in one click. Every promotion is audited, diffable, and reversible.

Get in before launch.

Zahara is the control plane and harness for teams shipping agents into production. Pick your track below.

Models create capability. Zahara creates deployability.

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