Understand & plan
You describe a goal in natural language. The CEO AI builds an internal understanding of the task and breaks complex requirements down into a task graph with dependencies, priorities, and alternative paths.
Product
One assignment, planned, delegated, and verified by an artificial software team
Argo is a complete work environment for software development, analysis, planning, quality assurance, and knowledge management — not a chatbot. Projects are bound to local folders, every execution is a traceable run, and results only count as done once they've been verified.
What Argo is
Our CORE AGENT technology
A standalone architecture that runs locally on your device and plans, delegates, executes, and verifies complete work assignments. Your code and knowledge stay with you. Cloud providers and local models run side by side under the BYOK principle (Bring Your Own Key) — no lock-in to a single vendor.
- CORE
-
The engine that understands, plans, and reasons through your task.
Collaborative Orchestration & Reasoning Engine
- AGENT
-
Coordinated AI experts working together as a team.
Aligned Generative Experts in a Networked Team
- Context intelligenceView tier availability — a tree-sitter-based index delivers targeted context packages instead of whole repos
- Memory & Skills — project-specific knowledge and recurring work patterns are captured and versioned
- Dream Mode — idle time is used to automatically consolidate and clean up stored knowledge
- Team license & LAN syncView tier availability — devices on the same license share knowledge over the local network, no cloud detour
- Signed updates — installation, repair, and updates run through cryptographically verified manifests
How it works
A complete development process, not a sequence of prompts
Planning, implementation, review, correction, and sign-off are separate responsibilities. Every run has its own policies, budgets, model decisions, and event logs.
Delegate & deliberate
Specialized roles — architecture, development, QA, documentation, verification — develop independent hypotheses, gather evidence, challenge each other, and revise their positions.
Verify & apply
Changes are produced patch-first in a sandbox or Git worktree and only applied after successful verification. Conflicts are detected, never silently overwritten.
Why Argo?
An orchestration and governance layer above any model
Argo doesn't try to beat every specialist at its own game. It's the orchestration and governance layer sitting above any model — the actual product is a resilient, verifiable, learning process for agentic software development.
Generation and verification are separate
A single agent quickly delivers a plausible solution — and occasionally fails spectacularly. Argo separates generation from verification: tests, reviews, verification steps, and independent checkers decide when something is actually done. That shifts the quality distribution upward.
No lock-in, the best combination
Cloud providers and local models run in parallel, deployed by strength. API keys stay encrypted on your device. Model selection isn't a black box — you see which models were considered, which were excluded, and why.
You set the level
Plan only, ask before every change, small changes automatically, or broad permissions — finely graded. High-risk actions like critical commands, deletions, or downloads always stay specially protected, even at high autonomy levels.
Collaboration because it demonstrably helps
Argo compares the agent team's performance against the best single agent and measures the quality gain as a Collective Intelligence Lift. An eval infrastructure with regression tests and a Quality Lab judges improvements against metrics, not impressions.
Economics
Does it pay off?
Yes — but measured against the right metric. Not "cost per request," but "cost per accepted result." Argo deliberately invests extra checks and tokens to save retries, rework, and review time — human labor is the resource that's expensive by orders of magnitude.
- Routine work runs on cheap or local models; frontier models only where the added value justifies the cost
- Budgets enforceable as soft or hard limits, with effort and quality simulated before a run starts
- Honestly: Argo is overkill for fixing a typo — the payoff grows with complexity, the cost of mistakes, and project duration
Run timeline
Context sources, model decisions, costs, file access, checks, error handling.
Context sources, model decisions, costs, file access, checks, error handling.
View tier availabilityReplay
Trace why a decision was made and which agents were involved, long after the fact.
Trace why a decision was made and which agents were involved, long after the fact.
View tier availabilityAudit export
Redaction profiles for technical evidence, compliance documentation, and support packages.
Redaction profiles for technical evidence, compliance documentation, and support packages.
Who it's for
For teams that need more than a coding agent
Argo is built for users and teams who need verified results with controllable risk and measurable quality — not just more autonomy. Seven editions from Free to Enterprise cover that range, from trying it out to a large dev team with SSO and central administration. Details on the pricing page.
Software development
Refactors, migrations, features, root-cause analysis, tests — the strongest use case.
Refactors, migrations, features, root-cause analysis, tests — the strongest use case.
Quality & security
Reviews, defensive security analysis, compliance evidence, audits.
Reviews, defensive security analysis, compliance evidence, audits.
Knowledge work
Architecture decisions, technical research, data analysis, documentation.
Architecture decisions, technical research, data analysis, documentation.
Structure and memory a single model doesn't have
Argo adds structure, memory, division of labor, critique, verification, and process discipline to what modern models can already do — see all use cases in detail on the capabilities page.
The installer sets up Argo and keeps it current — updates, repair, and uninstall included.