Verified agent systems
Each system is expected to expose its architecture, agents, tools, approval gates, risks, test results, maturity status, and last verification date.
View maturity registryA TRUSTED REFERENCE FOR AGENTIC AND MULTI-AGENT AI
Trust in agentic AI should be earned.
Explore reference architectures, verified maturity records, interactive simulations, reproducible tests, and governance patterns built around one principle: powerful AI should remain visible, accountable, and under meaningful human control.
170 multi-agent systems.
One transparent standard for testing and promotion.
Human authority preserved by design.
170
reference architectures
15
engineering domains
10
Gold Standard pillars
100
readiness points
THE QUESTION BEHIND THE WORK
Your agents may be capable.
Are they governable?
Specialization
Orchestration
Tools
Memory
Evals
Observability
Security
Human Authority
Provenance
Lifecycle
THE OFFICIAL ATLAS FIELD GUIDE
The engineering story behind the Atlas.
This standalone field guide connects the 170 reference architectures, ten flagship simulations, public Demo Lab, Gold Standard, repository code, evaluation methods, and human authority model into one professional engineering resource. It establishes the public evidence while organization-specific implementation remains private professional work.
95 pages
25 chapters
11 appendices
A DESIGN POSITION
The model is not the system.
A production agent is the model plus the tools it can call, the memory it can retain, the permissions it can exercise, the evidence it can access, the failures it can trigger, and the humans who remain accountable. This project studies that larger engineering surface.
FIVE LAYERS OF TRUST
Trust is not a badge. It is a record anyone can inspect.
The library is built around visible evidence, consistent evaluation, reproducible behavior, and meaningful human authority. These are the commitments behind every maturity claim.
A public evaluation framework
Transparent scoring covers reliability, safety, evidence quality, human oversight, failure handling, observability, reproducibility, security, documentation, and production readiness.
Inspect the standardEvidence behind every claim
Technical claims should trace to primary research, official documentation, standards, or reproducible results, with established evidence separated from interpretation and experimental work.
Inspect the sourceReal demonstrations
Scenarios make coordination visible through agent roles, evidence and tool traces, failure cases, human approval points, and downloadable results.
Enter the Demo LabIndependent credibility
Public issues, named contributors, version history, citation guidance, a correction path, and transparent limitations make the work open to scrutiny and improvement.
Review or challenge the workThe standard is simple: do not ask people to trust what they cannot inspect.
THE ARCHITECTURE ATLAS
Do not browse 170 repositories. Navigate a field.
The Atlas turns the full library into a searchable reference. Filter by domain, search by system name or problem, compare architectures, and open any standalone repository directly. It is designed to be useful enough to bookmark, teach from, cite, challenge, fork, and return to.
Use it to
- Compare multi-agent decomposition across domains
- Study orchestration, memory, tools, and evaluation
- Inspect protected-action and human-approval patterns
- Find reference systems for research and teaching
- Fork architectures and test alternative designs
- Trace every entry to its standalone repository
THE SELECTED FLAGSHIP PORTFOLIO
Ten systems selected to turn architectural breadth into visible proof.
The flagship portfolio concentrates the strongest commercial and demonstration opportunities from the full Atlas. Each system must show working coordination, a failure challenge, traceable evidence, and a protected decision that remains under human authority.
Selected for
- Market demand and identifiable buyers
- Differentiation from generic assistants
- Implementation and evaluation potential
- Strong visual demonstration value
- Enterprise assessment and implementation potential
THE AGENTIC AI GOLD STANDARD
Ten disciplines for systems that operate beyond the chat window.
Specialization
Clear roles, responsibility boundaries, escalation, and prohibited authority.
Orchestration
Explicit workflow control, handoffs, retries, failure states, and bounded autonomy.
Deterministic Controls
Typed tools, validated inputs, policy gates, structured state, and idempotency.
Memory Governance
Scoped retention, provenance, correction, deletion, and sensitive-data boundaries.
Evaluation
Held-out tests, adversarial scenarios, regression gates, and acceptance criteria.
Observability
Traceable decisions, tool calls, approvals, failures, and external actions.
Safety & Security
Least privilege, data minimization, injection resistance, and defensive controls.
Human Authority
Protected actions, meaningful approvals, decision rights, and accountable execution.
Provenance
Evidence lineage, source fidelity, reproducibility, and auditable decision records.
Lifecycle Governance
Release criteria, rollback, incident response, ownership, and continuous improvement.
L3 Gold Standard is an engineering maturity designation defined by this project, not a regulatory certification or legal compliance determination.
READINESS SCORECARD
How much authority can your architecture actually support?
Twenty engineering questions create an initial maturity estimate. The score is directional. The more important result is where the architecture lacks evidence, boundaries, or fail-closed behavior.
Experimental 0-39
Emerging 40-59
Managed 60-74
Production Candidate 75-89
Gold Standard Candidate 90-100
0
/100
ENTERPRISE WORK
For teams moving from agent demos to accountable systems.
Readiness Assessment
Independent architecture and governance review.
Gold Standard Gap Review
Focused remediation planning toward production maturity.
Architecture Sprint
Design orchestration, tools, memory, evaluation, observability, and authority.
Evaluation & Governance
Build tests, traceability, authorization, and release infrastructure.
Executive Workshops
Align leadership, engineering, security, risk, legal, and product.
Advisory
Ongoing support for organizations scaling agentic AI.
MULTI-AGENT AI TRAINING
Build the capability to design accountable AI teams.
Live training for enterprise teams, technical leaders, engineers, universities, and professional organizations, from executive briefings to applied engineering bootcamps.
Available formats
- Executive briefings
- Half-day and full-day workshops
- Engineering intensives
- Applied multi-week bootcamps
- Custom enterprise enablement
FOUNDING PARTNER PROGRAM · THREE OPENINGS
Build the AI team your highest-value workflow actually needs.
Selected organizations receive a focused multi-agent architecture, governed prototype, evaluation evidence, and an implementation roadmap with human authority designed in from the beginning.
Founding engagement
- Workflow and authority mapping
- Specialized agent architecture
- Governed interactive prototype
- Normal and failure-mode evaluation
- Executive implementation roadmap
START A CONVERSATION
Bring the architecture you actually have.
Share the system at a high level. The first conversation is about scope, authority, evidence, and where production risk is concentrated.
Private lead routing
No public GitHub issues
No credentials or secrets
No sensitive uploads
Privacy: Do not submit passwords, API keys, protected health information, customer records, classified information, trade secrets, or confidential source code.
FROM ATTENTION TO EVIDENCE
Do not take the Atlas at its word. Inspect how it reaches a boundary.
The public proof layer connects interactive scenarios to architecture, evidence status, limitations, and the decisions that remain protected by human authority.
FLAGSHIP EVIDENCE
See exactly what each flagship demonstrates.
Review the public evidence, current status, limitations, architecture, simulation, and maturity boundary for all ten flagship systems.
Inspect flagship evidenceATLAS CHALLENGE
Can you find the failure before the agents act?
Examine synthetic multi-agent traces and identify the missing evidence, unsafe handoff, or protected action that should stop the workflow.
Take the challengeA PUBLIC REFERENCE, BUILT TO BE USED
Explore it. Test it. Challenge it. Build on it.
If the Atlas helps your research, teaching, architecture work, or production thinking, bookmark it, star the source library, and share the system that was useful.