NeueCode vs PUMAS: Runtime Governance vs the Full Sovereign Stack

What PUMAS does well

PUMAS — “Policy-Unified Monitoring, Audit & Security”, per its own page title — describes eight modules forming one runtime governance layer: agent discovery that builds a live registry of every agent, model, API, MCP server, tool, and secret, surfacing shadow AI your organization never approved; runtime monitoring of prompts, tool calls, model usage, DNS, and outbound traffic; policy enforcement at the moment of execution with allow, block, escalate, and approve verbs; an “immutable, queryable, cryptographically-verifiable” audit trail; compliance posture against HIPAA, PCI DSS, GDPR, NIST AI RMF, SOC 2, and VARA; AI data-loss prevention; incident management that can auto-isolate agents and route to your SOC; and a control dashboard — all, by its own positioning, deployed inline without changing your agents’ code. Its team page states it was founded by operators from enterprise security — its CEO Dubai-based with a deep network across the UAE and GCC — and that it works directly with enterprise security and compliance teams as design partners. Its stated principles — “Policy is the primitive”, “Audit is non-negotiable” — are coherent and serious. A second product, Mongoose, addresses developer-and-agent productivity telemetry with a privacy-first design: per its published description, no prompts or code ever leave the developer machine — only counts, durations, and outcomes. For an enterprise with a sprawling, multi-vendor agent estate, that agent-agnostic breadth is genuinely valuable.

Two different questions: govern what exists vs build, serve, and govern

By its own positioning, PUMAS is not an agent builder — it explicitly states it is “not a model-safety tool, not another static GRC platform” — it is the enforcement layer that sits between the agents your organization already runs and the systems they touch. That focus is its strength, and it defines the boundary of what it does: the agents themselves, and the models behind them, are built and hosted elsewhere. NeueCode 7 — the Govern AI Autonomous Enterprise System — spans all three layers as one product: it builds the engineering agents (a bounded agent loop with human approvals, reviewable diffs, and named sub-agents for research, analysis, systems work, and code review); it serves local open-weight models on your own GPUs through a VRAM-aware gateway; and it governs — an AI Governance Gateway that inspects, redacts, blocks, and signs an audit record of traffic from external assistants such as GitHub Copilot, Cursor, and Claude Code, a deny-by-default egress broker, a Feature Registry that locks capability classes per principal, and break-glass dual control requiring two people for emergency overrides. That is an architectural difference, not an accusation: PUMAS governs flows to wherever your agents already send data; NeueCode’s inference is local by construction, so the most sensitive flow — source code to model — never forms an external leg at all.

Two kinds of audit evidence — both real

Credit where due on both sides. PUMAS describes its audit trail as an “immutable, queryable, cryptographically-verifiable record of every action and decision”, and holds that “every autonomous action must leave verifiable evidence” — a principle NeueCode shares. The difference is what the evidence is about. PUMAS’s record, per its published pages, is evidence about the agents it observes and enforces upon. NeueCode’s evidence covers the platform’s own behavior: a tamper-evident, hash-chained Agent Flight Recorder that your own auditor verifies offline — neither NeueCode nor your operators sit in the trust path — and, in strict mode, a deny-by-default egress broker that signs an offline-verifiable, per-run non-egress manifest: proof that the agent’s own code paths sent nothing out, not only observation of what others sent. Both vendors reach for the same honest verb — mapped. PUMAS states mapping to the EU AI Act, NIST AI RMF, ISO/IEC 42001, DORA, GDPR, HIPAA, PCI DSS, SOC 2, and VARA; NeueCode maps — not certifies — its evidence export to the EU AI Act, DORA, NIS2, SOC 2 CC6, ISO 42001, and, for Gulf buyers, SAMA and NCA. A regulated buyer will likely want both kinds of evidence — what your agent estate did, and what your engineering platform can prove about itself.

Sovereignty and deployment: stated vs unstated

NeueCode publishes its deployment model plainly: on-premise up to fully air-gapped, on your own servers and GPUs, with updates delivered as signed offline packages and internet-reaching capabilities locked off in strict mode. PUMAS’s published pages describe an inline deployment — “PUMAS sees every request before it executes” — but do not state where the PUMAS control plane itself runs: no on-premises, self-hosted, or air-gapped deployment claim appears in its published materials, and no cloud statement either. That is an absence in published materials, not a finding — a buyer evaluating PUMAS should simply ask, and may well receive a satisfactory answer. But for an air-gapped estate the question is decisive: a governance layer must live where the governed workloads live. On regional fit, both vendors are serious about the Gulf — PUMAS states VARA mapping, and its team page cites a Dubai-based CEO with a deep GCC network; NeueCode is Kuwait-first for the GCC, ships native English and Arabic with full RTL in the product, and maps evidence to SAMA and NCA for Saudi buyers.

Commercials, coexistence — and how to choose

NeueCode’s commercial model is public and simple: one licence per active server, unlimited developers, no per-token bills — a number finance teams can budget for an entire engineering organization. PUMAS publishes no pricing on its pages; that is an absence, not a criticism — many enterprise vendors price by conversation. It is also worth saying plainly: these two systems are not mutually exclusive. An organization could run PUMAS as an estate-wide monitor over the SaaS copilots and cloud agents it already has, while NeueCode 7 runs the engineering work on repositories that can never leave the network — each producing its own audit evidence. Choose PUMAS if your problem is a sprawling, multi-vendor agent estate across SaaS and cloud that needs discovery, monitoring, and runtime enforcement without changing agent code — by its own positioning, that is precisely its design center. Choose NeueCode when source code cannot leave the network; when you want the agents, the models, and the governance as one sovereign per-server system rather than a control plane over systems built elsewhere; when auditors need offline-verifiable evidence of the platform’s own non-egress; or when Arabic-first GCC deployment and air-gapped operation are requirements, not preferences.

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