| What it does | Enterprise AI system of record for governing and operationalizing AI at scale
| AI execution infrastructure that turns mission-critical manual tasks into reliable, paid AI services
|
|---|
| Stage | Established
| Not given
|
|---|
| Founded | 2018
| Not given
|
|---|
| Based in | US
| Not given
|
|---|
| Pricing model | Contact for pricing
| Contact for pricing
|
|---|
| Pricing | Not given
| Not given
|
|---|
| Key features | - Centralized system of record across every model, solution, and agent
- Automated workflows with governance embedded by design
- Full portfolio visibility into cost, tokens, risk and ROI
- Dynamic interoperability across 50+ technologies
- Connective automation for IT, business, and AI owners
- Agentic-powered framework for end-to-end AI lifecycle workflows
- Operational intelligence across ML, GenAI, agentic and vendor AI
- Audit-ready evidence mapped to every regulation and policy
| - Job of Work Mapper: identifies valuable processes and maps required outcomes, steps, systems and stakeholders
- Execution Engine: manages multi-week or multi-month workflows with fault tolerance, checkpoints and error recovery
- Built-in stakeholder management: communicates with stakeholders across channels and escalates exceptions
- Intelligence flywheel: captures execution data to benchmark models, improve accuracy and optimise costs
- Small focused AI models in deterministic graph: reduces errors and cost vs single large models
- Fully auditable and explainable execution
- Durable execution engine with checkpoints and automated recovery
|
|---|
| What makes it different | - Brings ML, GenAI, and agentic AI to production 10× faster
- System of record that unifies every AI asset in one place
- Reduces time from idea to production to weeks at industrial scale
- Enforces policy and governance at delivery time, not in committee
- Operates above existing systems without replacing them
| - Handles multi-stakeholder workflows spanning days, weeks or months without requiring core product rebuild
- Partners keep control of brand and customer relationships while using platform for execution
- Usage-based pricing aligns fees with completed outcomes rather than features
- Small focused AI models designed for accuracy and repeatability in high-trust workflows
- Includes mapping stage to validate commercial viability before significant investment
|
|---|
| Community votes | 0 | 0 |
|---|
| DR (Domain Rating by Ahrefs) | 62 ● no change since last check | 12 ● no change since last check |
|---|
| Trust Flow (Majestic) | 13 | 8 |
|---|
| Citation Flow (Majestic) | 39 | 29 |
|---|
| Referring domains (Majestic) | 579 | 64 |
|---|
ModelOp
Aguru