jackfruit.ai

The Agentic Readiness Framework.

Jackfruit Framework

18 dimensions · 258 checks · 6 pillars

Infrastructure

4D · 63C

Data

2D · 27C

Operations

3D · 38C

Security

2D · 20C

Governance

3D · 32C

Discoverability

4D · 31C

Defining Agent Readiness

Six pillars.
One living system.

Agent readiness is the measurable capacity of a company's stack to support autonomous AI workloads. From API contracts and identity to governance and external discoverability. Six interconnected pillars, 18 dimensions, 258 checks.

The Agentic Readiness Standard

Explore all 18 dimensions and 258 checks that define enterprise readiness for autonomous AI agents. Select any dimension to see its checks, assessment criteria, and how each capability is evaluated.

This page publishes full L0-L3 definitions for 211 of the framework's 258 checks. The remaining 47 are scored, but their public definitions are still being written. Some checks require privileged access or interview evidence and are only reachable at the higher assessment tiers — see Assessment Depth below.

Infrastructure4D

Evaluates how well your APIs and interfaces are structured for autonomous agent consumption. Covers specification coverage, idempotency, error semantics, rate limiting, versioning, protocol support, pagination, input validation, and throughput readiness.

Data2D
Operations3D
Security2D
Governance3D
Discoverability4D

Assessment Depth

ARF assessments come in four tiers. Each tier unlocks deeper analysis by accessing more data sources.

T1

T1 — Public Scan

Automated analysis of public web properties, APIs, documentation, and external digital presence. Available for all organizations.

Coverage loading…

T2

T2 — Code Scan

Repository-level scanning via GitHub integration. Reveals internal architecture, security practices, CI/CD maturity, and code-level patterns.

Coverage loading…

T3

T3 — Cloud Scan

Cloud infrastructure scanning via a connected AWS account. Reveals runtime configuration, IAM policies, and cloud-native practices.

Coverage loading…

T4

T4 — Enterprise Scan

On-site assessment, manual review, and enterprise integration. Full coverage including governance and collaboration.

Coverage loading…

T1Public Scancounting…

Probing public APIs_

Covers

APIsDNSCertificatesSecurity HeadersDocsDigital Presence
T2Code Scancounting…

Analyzing CI/CD configs_

Unlocks

RuntimeSupply ChainKnowledge MgmtThreat Defense
T3Cloud Scancounting…

Reading cloud logs_

Unlocks

Cloud InfraIAMNetworkingDevOpsIntegration
T4Enterprisecounting…

Inspecting architecture_

Unlocks

GRCAgent EconomicsHuman-Agent CollaborationArchitecture Review

Agentic Readiness Level

The reported grade for every check is its L0–L3 maturity level, defined in the framework’s contractual rubric. The Agentic Readiness Level (ARL) — a 10-stage scale (0–9) — is an intermediate signal collapsed into that grade, and stages 6–9 are not distinguished in the score.

Each ARL stage captures a concrete checkpoint on the path from “no signal” to “agent-native” capability: wired into the request path, hardened in CI, production-observed, contracted, and ultimately exposed as a capability that other agents can negotiate against.

0
No signal. No artefact, no doc, no public intent.
1
Public intent. RFC, blog post, or roadmap names the capability.
2
Contract or schema declares the capability.
3
Code or config for the capability exists in source.
4
Live in the production request path.
5
Behaviorally correct on the happy path.
6
Negative paths covered by CI tests.
7
Production observability + named incidents resolved.
8
Versioned public contract with deprecation policy.
9
MCP/A2A capability surface other agents can negotiate against.
Each stage marks a concrete checkpoint on the path from no signal to agent-native capability. Hover any stage to read the bar to clear.

Internal-state-heavy dimensions (state management, data, governance ops) have published external-observability ceilings below ARL 9; above the ceiling, organisations attest higher stages with workspace evidence.

Why Agentic Readiness Matters

95% of enterprise infrastructure was built for human operators, not autonomous agents. The gap is existential.

Agents don’t retry politely. They fail catastrophically on undocumented APIs, missing permissions, and brittle state management.

The companies that prepare their infrastructure now will dominate the agentic economy. The rest will be left behind.

Self-assessment is unreliable. Only automated, evidence-based evaluation reveals true readiness.

0

Pillars

Infrastructure, Data, Operations, Security, Governance, Discoverability

0

Dimensions

Grouped across 6 pillars — Infrastructure, Data, Operations, Security, Governance, Discoverability

0

Checks

Granular, automated assessments with evidence

Get Your Assessment

See how your infrastructure scores across all 18 dimensions. Comprehensive. Actionable. Confidential.

Request a ReviewSee How the Industry Performs →

Missing Something?

Let us know if there’s a dimension, check, or area we should cover.

Jackfruit AIFramework Explorer

Beta — AI analysis is advisory, not a guarantee.

Suggested questions

Ctrl+K