Access & permissions
Set team boundaries, model access, and approval paths so the right people run AI work—with oversight built in.
Enterprise
Software engineering at scale for enterprises.
4RGE helps leadership teams move from AI experiments to durable delivery—shorter cycles, clearer accountability, and visibility across the portfolio without betting the company on hype.
Feature Delivery
7x
faster
Migration Time
96.1%
reduction
On-call Resolution
95.8%
time saved
Enterprise platform
Data speaks for itself.
Built for large enterprises
AI orchestration
Run agents, models, and workflows through one shared platform so parallel delivery scales without losing ownership or status.
Governed execution
Apply policies, spend limits, and review gates before output reaches production—keeping people in the loop on critical decisions.
System connectivity
Connect repositories, MCP servers, APIs, and internal tools so AI extends how your teams already ship and operate.
Enterprise partnership
Work with 4RGE on rollout planning, escalation paths, and executive alignment as programs move from pilot to production.
Operational visibility
Follow activity, usage, and rollout progress across teams and business units from one control plane—not scattered status updates.
Integrations
Native Integrations
We support every major language, MCP plugins, and development frameworks—and integrate seamlessly with the tools your team relies on.
View allSecurity
Industry-grade security andcompliance
4RGE protects your IP, source code, and agent activity with enterprise-grade controls—access policies, audit trails, and data handling built for regulated teams.
Infrastructure
We own the compute.
The same company building the intelligence controls the infrastructure that runs it.
- TrainerDedicated B200 training jobs
- InferencerLow-latency serving
- HarnessHigh-throughput agent runs
Local-native agent infrastructure
Agent execution lives on the user’s machine — not inside a third-party cloud environment.
Local
Device
Agent harness
The 4RGED agent harness executes natively on the user’s device, keeping repositories, tools and execution within the local environment.
RepoToolsRuntime
Local execution
The 4RGED agent harness executes natively on the user’s device, keeping repositories, tools and execution within the local environment.
Local
Device
Agent harness
The 4RGED agent harness executes natively on the user’s device, keeping repositories, tools and execution within the local environment.
RepoToolsRuntime
Local execution
The 4RGED agent harness executes natively on the user’s device, keeping repositories, tools and execution within the local environment.
Local
Device
Zero retention
Agent execution and context remain native to the user’s system. Sensitive code, files, credentials and working context are not stored by 4RGED or in third-party cloud infrastructure.
Context staysZero retention
Zero-retention by design
Agent execution and context remain native to the user’s system. Sensitive code, files, credentials and working context are not stored by 4RGED or in third-party cloud infrastructure.
Local
Device
Owned knowledge
Context is built and maintained within the user’s system, allowing agents to work with enterprise knowledge without transferring ownership of that knowledge to the platform.
Owned knowledgeOn-device
Privacy by architecture
Context is built and maintained within the user’s system, allowing agents to work with enterprise knowledge without transferring ownership of that knowledge to the platform.
Dynamic prompt orchestration
- 4RGED composes the right prompt for the right agent — adapting instructions to task complexity, model capability, context and execution requirements.
- User intent + codified knowledge + dynamic prompting = more focused reasoning, consistent execution and better agent output.
Tailored prompts
Codified prompt modules are assembled in real time around the user’s instruction, selected model, task complexity, available context and required depth of reasoning — giving every agent a purpose-built execution framework.
12-dimension comparison
Enterprise intelligence platform comparison
| 4RGED | Claude | |
|---|---|---|
| Platform | 4RGEDVertically integrated intelligence platform — models, agents, context, compute, governance and product surfaces in one system. | ClaudeFrontier AI platform centered on Anthropic's Claude models, with Claude Code as its agentic coding environment. |
| Intelligence | 4RGEDOwn 4RGE model family — Magma, Blaze and Ember — combined with leading external models through one intelligence layer. | ClaudeAnthropic's proprietary Claude model family. |
| Model Orchestration | 4RGEDChoose, route and optimize intelligence across models based on task, context, performance and economics. | ClaudeWorkloads operate primarily within the Claude model ecosystem. |
| Context & Knowledge | 4RGEDOrganizational intelligence spanning repositories, projects, users, agents and models — designed to preserve and compound useful context. | ClaudeStrong codebase and project context, expandable to external systems through MCP. |
| Surfaces | 4RGEDDesktop · CLI · Web · Mobile — connected to the same intelligence, context and enterprise control plane. | ClaudeClaude Code across terminal and IDE workflows as extensions rather than fully native systems. |
| Enterprise Observability | 4RGEDCross-model, cross-surface visibility into users, teams, projects, consumption, cost, performance and utilization. | ClaudeClaude provides detailed API cost/usage reporting and telemetry metrics. |
| Governance | 4RGEDOne control layer for model access, users, teams, projects, budgets, policies and agent behaviour. | ClaudeEnterprise roles, permissions, settings and administrative controls across the Claude environment. |
| Compute | 4RGEDDedicated B200 clusters and 4RGED-controlled inference infrastructure — model architecture and compute engineered together. | ClaudeClaude inference is delivered through Anthropic and supported enterprise/cloud deployment infrastructure. |
| Economics | 4RGEDOptimizes the entire intelligence cost path — model architecture → context → routing → inference → compute → application. | ClaudeEconomics are principally determined by Claude model selection, token consumption, caching and Anthropic pricing. |
| Private / Sovereign AI | 4RGEDDesigned for dedicated, private and jurisdiction-specific infrastructure — including sovereign deployment patterns for regulated environments. | ClaudeStrong enterprise privacy controls; qualified Claude Code Enterprise accounts can receive Zero Data Retention. |
| Enterprise Execution | 4RGEDCodified prompts, institutional knowledge, policies and workflows can become reusable operating instructions for every agent. | ClaudeClaude Code supports configurable agent behaviour, settings and integrations within Claude workflows. |
| Bottom Line | 4RGEDOwn the intelligence. Own the context. Own the compute. Control the economics. Deliver it everywhere. | ClaudeFrontier intelligence delivered through the Claude ecosystem. |
Scores reflect architectural fit for enterprise platform ownership, not model benchmark performance. Updated for 2026 product surfaces.