jev-review vs Poolside AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-09-22
Cross-checked through our multi-step verification ·
Saved

At a glance

Dimensionjev-reviewPoolside AI
PricingFree, MIT-licensed (plus TypeSafe API key)Contact sales — no published tier
What it isCLI + local dashboard code-review workflowOpen-weight models + agentic platform
ModelsNone — orchestrates external model callsLaguna XS 2.1 (33B), Laguna S 2.1 (118B, 1M context)
DeploymentLocal, dashboard bound to 127.0.0.1:4317On-prem / air-gapped / multi-cloud inside perimeter
IntegrationsGitOpenRouter, Vercel AI Gateway, repo/DB/warehouse connectors
GovernanceThresholds and policy in code, inspectable end to endRBAC, audit trails, end-to-end agent trace observability
jev-review
jev-review

Open-source, MIT-licensed TypeScript code review that runs staged AI judgments over a Git diff or whole codebase and shows results in a local dashboard.

Visit Website
Poolside AI
Poolside AI

Open-weight agentic coding models — Laguna XS 2.1 and Laguna S 2.1 — built for secure on-prem and air-gapped enterprise AI.

Visit Website
Pricing
Free
Contact Sales
Plans
Free
—
Popularity
4 views
7.1k views
Skill Level
Intermediate
Advanced
API Available
Platforms
DesktopCLI
DesktopCLIAPIWeb
Categories
🔎 Code Review & Quality💻 Code & Development
💻 Code & Development🛠️ Autonomous Coding Agents⚛️ Foundation Models & LLM APIs🛡️ AI Governance & Guardrails
Features
Staged code-review workflow with orchestration kept in TypeScript code
Noul risk matrix feeding Choice and Score file profiles
Choice evidence selection across concrete diff hunks or source regions
Choice mechanism classification followed by Score severity scoring
Conditional Choice reviewer routing driven by prior judgments
Separate entry points for change review and complete-codebase scan
Uses changed or related tests as context when judging test gaps
Screens correctness, security, reliability, compatibility, and test coverage
Structured hints, counterexamples, and explicit decision boundaries in prompts
Thresholds and workflow policy applied in code, not in the model
Local dashboard bound to 127.0.0.1 that never serves environment files
Collapsible dashboard sections for large reports
CLI output as JSON via review:changes and review:codebase
Layer-enforced architecture checked by scripts/check-dependencies.ts
npm run check typechecks, verifies dependency flow, and syntax-checks the dashboard client
Laguna S 2.1 open-weight model: 118B params, 8B active, 1M context
Laguna XS 2.1 open-weight model: 33B params, 3B active, 256K context
Laguna XS 2.1 designed to run on-device for lightweight scenarios
Laguna S 2.1 positioned for frontier-class long-horizon reasoning
Single-agent and multi-agent orchestration with planning and tool use
Sandboxed agent execution environments for running generated code safely
Desktop app and CLI for agentic coding sessions
Model selection, tool grouping, and project management in the client
Data connectors to repositories, databases, and warehouses
Role-based access control for both human users and agents
End-to-end trace observability for agent runs
Governance and auditability built for regulated environments
Custom model fine-tuning on domain-specific data
Deployment inside your security boundary: on-prem, VPC, or workstation
Access to Laguna models via OpenRouter and Vercel AI Gateway
Integrations
Git
OpenRouter
Vercel AI Gateway

Feature-by-feature

The two products barely occupy the same functional layer. Jev Review is a review pipeline: it keeps orchestration in TypeScript and hands the model a chain of bounded judgments — a Noul risk matrix feeding Choice and Score file profiles, Choice evidence selection across concrete diff hunks or source regions, mechanism classification, severity scoring, and conditional reviewer routing. Two entry points cover change review and complete-codebase scanning, and it screens correctness, security, reliability, compatibility, and test coverage, reading changed or related tests when judging test gaps. Policy and thresholds live in code, not in the model.

Poolside AI is the layer beneath that: it ships open-weight coding models plus the platform around them. Laguna XS 2.1 is 33B params with 3B active and a 256K context, sized for on-device use; Laguna S 2.1 is 118B params, 8B active, 1M context, aimed at frontier-class long-horizon reasoning. Around the models are single- and multi-agent orchestration with planning and tool use, sandboxed execution for generated code, a desktop app and CLI, data connectors to repositories, databases, and warehouses, RBAC for humans and agents, and end-to-end trace observability. Jev Review asks what a model should be asked, in what order, and how the answer is scored; Poolside supplies the model, the agent runtime, and the governance wrapper.

Pricing compared

Jev Review is free and MIT-licensed — there is no license cost, and you supply your own TypeSafe API key, so your real spend is that API usage plus the Node.js 24+ environment you already run. That is an unusual amount of workflow for zero dollars, and it is the entire reason a solo developer can evaluate it today.

Poolside AI has no published price at all: pricing_type is contact, and the company's own positioning says there is no self-serve free trial or instant sign-up, and that buyers needing a publicly listed per-seat number before budget approval are not a fit. What you do get to compare is total ownership — with open weights you can inspect, fine-tune, and host Laguna models yourself, and the platform's RBAC, audit trails, and trace observability exist to satisfy regulated procurement. That is enterprise deal pricing, not a subscription line item, and the news that Nvidia agreed to pay Poolside a $6B license (Bloomberg, per an anonymous source) says more about the vendor's strategic position than about what you would pay. The honest comparison is zero dollars plus your own API key versus a negotiated enterprise contract — which is not a comparison a single budget can hold.

Who should pick which

  • Solo developer or open-source maintainer
    Pick: jev-review

    Free and MIT-licensed, runs on your machine, and the dashboard is bound to 127.0.0.1:4317 — you can be reviewing a diff tonight with only a TypeSafe API key.

  • Engineer who wants to read the review logic
    Pick: jev-review

    Orchestration, thresholds, and workflow policy are TypeScript you can read end to end, with structured hints, counterexamples, and explicit decision boundaries in the prompts.

  • Reviewer wanting a codebase-wide pass, not just a diff
    Pick: jev-review

    It ships separate entry points for change review and complete-codebase scanning, with collapsible dashboard sections for large reports.

  • Regulated engineering team in finance, healthcare, or defense
    Pick: Poolside AI

    Open-weight Laguna models can run on-prem or air-gapped inside your perimeter, with RBAC, audit trails, and end-to-end traces for agent runs.

  • Platform team with long-horizon multi-step refactors
    Pick: Poolside AI

    Laguna S 2.1 offers 118B params, 8B active, and a 1M context, paired with sandboxed agent execution and multi-agent orchestration.

Frequently Asked Questions

Could I use Jev Review with Poolside's Laguna models?

The data does not describe Jev Review's supported model providers, so that combination is unconfirmed. On its own terms, Jev Review requires a TypeSafe API key, and Poolside distributes its models via OpenRouter and the Vercel AI Gateway — nothing in either fact set confirms an integration between the two.

Is Poolside AI something an individual developer can just buy?

Based on its stated positioning, no: there is no published pricing tier and no self-serve free trial or instant sign-up, and the company explicitly names people wanting those as not a fit. Individual developers and small startups without an enterprise budget or procurement process are outside the target buyer.

What does Jev Review actually require me to install?

Node.js 24 or newer, Git, and a TypeSafe API key. It is MIT-licensed and runs locally, with the dashboard bound to 127.0.0.1:4317 and never serving environment files.

Do I need to own or run models to use Jev Review?

No. Jev Review is a review workflow that calls an external model; it does not ship or host its own model weights, and none of its listed features involve model training or hosting.

Does the Nvidia–Poolside news change Poolside's pricing?

There is no pricing detail in the report — it is a $6B license payment to Poolside attributed to an anonymous source via Bloomberg. Poolside still publishes no pricing tier, so nothing about what a customer pays has been established.

Which one is safer to point at a production repository?

That depends on your constraint, not the tool. Jev Review keeps everything local and never serves environment files, but it calls an external model API and its own materials warn against treating model findings as proof of a defect. Poolside is built for work that must stay inside a security boundary, with sandboxed execution, RBAC, and audit trails — at the cost of a procurement process and an unpublished price.

More jev-review or Poolside AI comparisons

Explore each tool further

Browse these categories

Still deciding? Get the weekly AI tools brief

One email a week — new tools, honest comparisons, no spam.

Last reviewed: September 22, 2026