What did Hlido score Network-AI?

Network-AI scored 76/100 (STEADY) in Hlido's independent, hands-on review.

How much does Network-AI cost?

Hlido recorded the pricing model as: Open source. Derived from evidence Hlido holds, not vendor-supplied; verify current prices on the vendor's pricing page.

Does any vendor pay Hlido for placement?

No. Hlido takes no money from the agents it rates — scoring weights stay private and the evidence behind every verdict is public.

Network-AI

Name: Network-AI review
Item: Network-AI
Rating: 76
Author: Hlido Editor

Frameworks & Eval · tested 2026-08-07 · re-test due 2026-11-07 · by the Hlido desk, not the vendor

In short: A governance layer for multi-agent systems that names the real failure mode — agents don't crash, they silently overwrite each other — and discloses its own high-severity CVEs on the front page.

5 PASS · 0 FAIL of 5 public-surface claims

Visit Network-AI → scorecard.json

Quick answer

Network-AI scores 76/100 (STEADY) on Hlido’s independent, hands-on test (reviewed 2026-08-07). STEADY (76) for a correctly-identified and under-served problem, primitives that actually address it (mutex-backed propose/validate/commit, permission gating, tamper-evident audit log), MIT licensing, and conspicuous sec Pricing: Open source (free entry point documented).

Hlido Editor · 2026-08-07

Network-AI sits between agents and shared state, adding locking, permission gating, budgets, audit trails and workflow governance so parallel agent systems behave like production software. The problem statement is the sharpest in this wave: parallel agents "do not usually fail loudly — they fail by silently overwriting state, bypassing policy, drifting across workflow stages, and leaving you with no reliable audit trail." That is correct, under-discussed, and exactly what most orchestration frameworks assume away. The primitives match it: propose→validate→commit with a filesystem mutex instead of last-write-wins, permission scoring before sensitive operations, and an append-only HMAC/Ed25519 tamper-evident audit log. It wraps existing agents (LangChain, CrewAI, AutoGen, MCP) rather than replacing them. What raises confidence most is uncomfortable: the release snapshot on the homepage is v5.15.1, headlined "Security: ClaudeHookBridge & SandboxPolicy matcher bypass fixes — two high-severity vulnerabilities." A security-governance product publishing its own high-severity bypasses on its landing page is behaving the way we want vendors to behave, and it also tells you the product is young enough to have shipped two policy-bypass bugs in consecutive releases. 3,638 tests across 41 suites and 32 adapters are self-reported and unverified. MIT licensed. Reviewed from the public surface.

Why STEADY

STEADY (76) for a correctly-identified and under-served problem, primitives that actually address it (mutex-backed propose/validate/commit, permission gating, tamper-evident audit log), MIT licensing, and conspicuous security honesty — it publishes its own high-severity fixes rather than burying them. Held below VITAL because those same disclosures show policy-bypass bugs in consecutive recent releases, every metric (3,638 tests, 32 adapters) is self-reported, and there is no third-party audit of a component whose entire value is enforcement.

Public-surface checklist

PASS Homepage loads (required)
PASS Primary value prop (required) — 'Orchestrate agents without trusting them blindly.'
PASS Cta present (required) — 'Read quick start' / 'Security posture'
PASS Pricing or access — MIT licensed, open source, npm-distributed
PASS Evidence or demo — Release notes with security disclosures, demos and journal; metrics self-reported

What we saw

4 screenshots captured by the Hlido engine during the reviewed run (run-be5ebff148cf15a4-network-ai-org). Our own captures — not vendor marketing material.

Network-AI — run screenshot 1 (home.png) — home.png

Network-AI — run screenshot 2 (page_architecture.png) — page_architecture.png

Network-AI — run screenshot 3 (page_proof.png) — page_proof.png

Network-AI — run screenshot 4 (page_demos.png) — page_demos.png

What it does well

Names the real multi-agent failure mode — silent state overwrites and policy bypass, not loud crashes
propose → validate → commit with a filesystem mutex instead of last-write-wins races
Permission-first execution: scores justification quality, trust level and resource risk before sensitive operations
Append-only HMAC / Ed25519 audit log — tamper-evident by design
Wraps existing frameworks (LangChain, CrewAI, AutoGen, MCP) rather than demanding a rewrite
Publishes its own high-severity security fixes on the landing page instead of hiding them
MIT licensed with zero adapter runtime dependencies

What it fails at

Its own disclosures show two high-severity policy-bypass vulnerabilities across consecutive releases — young enforcement code
3,638 tests / 41 suites / 32 adapters are all self-reported and unverified by us
No third-party security audit, for a product whose entire value proposition is enforcement
No named production users or adoption figures
Adds a mandatory layer between agents and state — a new dependency in the critical path
Not exercised by us; the locking and gating guarantees are untested

Red flags

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Best for

Teams running genuinely parallel agents against shared state who have hit silent overwrites
Regulated contexts needing a tamper-evident record of what an agent was permitted to do
Multi-framework estates wanting one governance layer rather than per-framework controls

Not recommended for

Single-agent or strictly sequential workflows, where the coordination cost buys nothing
Deployments requiring an audited enforcement layer today
Teams unable to absorb frequent security-driven upgrades

Pricing & access

ModelOpen source
Free entry pointYes — a free tier or open-source edition is documented
Pricing findable on the public surfacePASS MIT licensed, open source, npm-distributed (tested 2026-08-05)

Derived from Hlido-held evidence only (engine checklist + editorial text); quotes are verbatim from the scorecard; not vendor-supplied; re-derived daily. Verify current prices on the vendor's pricing page. Last verified 2026-08-05.

Related agents

Agent relevance

API MCP SDK Behavioral-testable

Agentic-Commerce Readiness 77/100 · COMMERCE-READY

Independent readiness for agent delegation & transaction. How it’s scored · check live

Purpose-built to sit in the agent execution path: adapters for LangChain, CrewAI, AutoGen and MCP, with control primitives (Blackboard, AuthGuardian, JourneyFSM, budgets) that agents call rather than humans.

Agent-friendly score: 9/10

Evidence

Multi-agent control plane adding locking, permission gating, budgets and audit trails — source (2026-08-07) verified
propose → validate → commit with a filesystem mutex — source (2026-08-07) verified
Append-only HMAC / Ed25519 tamper-evident audit log — source (2026-08-07) verified
v5.15.1 fixes two high-severity ClaudeHookBridge / SandboxPolicy bypasses — source (2026-08-07) verified
32 adapters, 3,638 tests, 41 suites, MIT licensed — source (2026-08-07)
Third-party security audit or named production users — source (2026-08-07)

scorecard.json · transparency passport · registry · methodology

More: compare agents · best of · developer tools · incident registry

Verdict by Hlido Editor, our automated editorial system · Method: public-surface-tier-1+editorial-narrative-v2 · Methodology version 2026.05 · Next review due 2026-11-07

How this page was produced. The scores, claim verdicts and evidence come from automated hands-on testing of the product’s public surface. The written analysis is drafted by an AI system, and pages publish without a person reviewing each one. Hlido publishes this record and answers for it — tell us if anything here is wrong and we will correct it.

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