The RIGOR Framework
We deliver governed autonomous intelligence grounded in published research. Not suggestions. Not assistants. Every autonomous action passes through five phases before it ships.
Benchmarks cited further down this page are from published research (e.g. ReAct, Yao et al.) and are clearly attributed; they are not Autonoma customer-runtime measurements.
Five Phases. Zero Assumptions. Pure Execution.
While others jump straight to code generation, RIGOR requires every autonomous action to be researched, inspected, generated, optimized, and reviewed. Every phase is logged and every action is reversible.
Research
Comprehensive context from multiple sources
Inspect
Safety audits and constraint validation
Generate
Artifacts with confidence scoring
Optimize
Feedback-loop refinement
Review
Systematic validation with auto-rollback
The Autonomous Era Doesn't Wait for Anyone
This isn't about if autonomous development takes over—it's about who leads.
Traditional AI Agents
Free-form generation, no pre-flight checks
No learning loop across actions
Manual rollback required
Missing critical context
Verification-First
Safety checks only
No optimization phase
Limited learning feedback
Static performance
RIGOR Framework
Research → Inspect → Generate → Optimize → Review on every action
Rollback-ready by design
Continuous learning across the loop
Full audit trail persisted per phase
Built on Peer-Reviewed Research, Not Hype
We don't ship assumptions. We ship systems validated by 25+ academic papers from 2022-2025.
Core Research Papers
Industry Validation
Own Your Incident Response. Permanently.
Transform or be transformed. Here's what RIGOR delivers in production.
Database Connection Pool Exhausted at 2 AM
Same Incident. Zero Human Intervention.
Where RIGOR Changes the Economics
Because every action is researched, inspected, and reviewable, incident-response loops that usually require a human war room can be scoped, executed, and rolled back by agents under audit. We don't publish cost-savings numbers we can't measure on your workload — ROI is modeled in the business case we build with you during onboarding.
Request an ROI walkthroughThree-Tier Capability System
Not every operation needs full RIGOR. We deliver the right level of autonomy for each use case.
| Tier | RIGOR Phases | Autonomy Level | Use Cases | Current |
|---|---|---|---|---|
| Tier 1 | R+I+G+O+R | Full autonomy, mission-critical | Self-Healing, Self-Deploying, Self-Protecting | 3 capabilities |
| Tier 2 | R+I+G | Standard automation | Self-Monitoring, Self-Optimizing, Self-Scaling | 13 capabilities |
| Tier 3 | R+I | Analysis & insights | Security scanning, analytics, reporting | Future |
Why tiers matter: Database optimization? Tier 2 (R+I+G). Critical security response? Tier 1 (full R+I+G+O+R). We match autonomy level to operational requirements.
Research Benchmarks RIGOR Is Built On
The published-research results that inform RIGOR's design. These are external benchmarks, not Autonoma customer-runtime measurements.
Autonoma uses these benchmarks as design targets. Customer-specific measurements will be published as they become available through opt-in runtime telemetry.
Governed Autonomous Development Starts with RIGOR
Gartner forecasts that a significant share of agentic AI projects will be scrapped by 2027 due to governance failures. RIGOR is our answer: every autonomous action is documented, auditable, and reversible.
Production-Ready, Observable by Default
9,950+ lines of production TypeScript. Zero assumptions.
Simple Integration
import { RigorOrchestrator } from '@/lib/rigor';
const orchestrator = new RigorOrchestrator();
// Full RIGOR cycle for critical operations
const result = await orchestrator.orchestrate({
tasks: [{
id: 'heal-db',
capabilityId: 'self_healing',
tier: 1 // Full R+I+G+O+R
}],
pattern: 'SEQUENTIAL',
mode: 'autonomous'
});
// Result includes:
// - Confidence scores
// - Reasoning traces
// - Automatic rollback on failure
// - Performance metricsObservable by Default
- Structured logs for every RIGOR phase
- Confidence scores on all decisions
- Reasoning traces for audit trails
- Automatic metrics collection
Safety First
- Multiple approval gates for critical operations
- 100% automatic rollback on validation failure
- Compliance checks (NIST, EU AI Act, SOC2)
- Human override always available
Technical Questions Answered
How does RIGOR compare to LangChain/AutoGPT?
LangChain is a framework for building agents. RIGOR is a methodology for making those agents reliable, safe, and continuously improving. You can use LangChain components within RIGOR.
Can RIGOR work with models other than Claude?
Yes. RIGOR is model-agnostic. We optimize for Claude Sonnet 4.5, but support GPT-4, Gemini, and other LLMs.
What's the latency overhead?
RIGOR adds phases for Research, Inspect, Optimize, and Review on top of raw generation. The overhead depends on the action — a quick code suggestion stays interactive, while a full incident-response loop may take longer in exchange for the audit trail and rollback path. Exact timing is reported per-action in your audit logs.
How much does RIGOR cost to run?
Cost depends on the model mix (Standard / Pro / Ultra tier) and how many phases a given action requires. The LLM Proxy tracks per-action cost and surfaces it in the billing dashboard — we do not publish a fixed per-operation price because it would not be accurate across workloads.
Can I disable RIGOR for certain operations?
Yes. RIGOR is opt-in per capability. Use Tier 3 (analysis only) or traditional automation where appropriate.
The Autonomous Era Is Here
Own your competitive advantage before others do.