Build the advantage. Put it to work.
MarutAI turns proprietary data and operating knowledge into customer-specific models, then gives teams the platform to build and run the agents, workflows, and services around them.
01 / Data foundation
Catalyst
Curates customer data and directs what the system needs to learn next.
02 / Model construction
VATS
Builds decision models and defines the conditions under which they can act.
03 / Build and operate
Manifest
Assembles and runs models, agents, workflows, services, and controls.
Decisions, reviews, boundary events, and outcomes return to Catalyst and strengthen the next model cycle.
Catalyst
Catalyst is MarutAI's recursive-learning data engine. It turns a customer's operational data and domain knowledge into a model-ready foundation, then identifies what the system needs to learn next.
Instead of treating training data as a one-time input, Catalyst keeps it useful as the business changes. Teams can see where the foundation is strong, where it is thin, and which next data investment will make the biggest difference to the model.
How Catalyst Works
- 01ConsolidateBring operational data, domain knowledge, policies, labels, and historical examples into a model-ready foundation.
- 02DiagnoseFind missing coverage, conflicting evidence, weak labels, and conditions the current data does not represent well.
- 03DirectSpecify what should be collected, generated, annotated, or validated next—and why it matters to the model.
- 04ReinvestReturn deployment evidence to the data foundation so every subsequent model cycle begins from a stronger base.
What Catalyst Delivers
Companies already own much of the knowledge that makes their operation different. Catalyst makes that knowledge usable for model development and shows where better data will make the biggest difference.
Model-Ready Foundation
Bring fragmented data, domain knowledge, and operating rules into one usable foundation for model development.
Faster Learning Cycles
Identify the gaps that will improve the model most, so teams know what to source, label, generate, or validate next.
More From Existing Data
Use the information the business already owns before spending time and money collecting more.
Better Real-World Performance
Improve coverage where the system actually operates, not only where historical data is easiest to find.
Customer-Specific Intelligence
Turn institutional knowledge and operating experience into an asset generic models cannot reproduce.
A Compounding Data Advantage
Every model and deployment strengthens the foundation behind the next one.
Manifest
Manifest is where customer applications are built and operated. Teams assemble models, agents, workflows, code, tools, connectors, and services into versioned solutions, then deploy them with the controls that carry failure knowledge and operating limits into the work they perform.
Customer-specific models built through VATS from data prepared by Catalyst can run alongside models from more than 90 commercial providers. Manifest carries their operating boundaries into the agents and workflows that use them and controls model routing, credentials, tool access, approvals, fallbacks, and escalation.
Governed actions can be traced from the data and model that informed them through the approval, constraint decision, and outcome. Manifest also monitors whether the assumptions behind a model still match operating conditions.
Core Capabilities
The Compounding Advantage
Each deployment creates proprietary evidence about the customer's operation. That evidence improves the data foundation, the models built from it, and the applications running on top of them.
- 01OperateManifest runs the models, workflows, services, and agents inside the customer deployment.
- 02CaptureCatalyst records the operating context, decisions, interventions, boundary events, and outcomes.
- 03ImproveCatalyst identifies the next knowledge gaps, and VATS uses the stronger foundation to construct and test the next models.
- 04ExpandThe improved system returns to operation, creating more evidence and a larger customer-specific advantage.
Customers gain more than a working application: they own a system shaped by their data, their decisions, and the way their operation actually runs.
Architecture
Build it once. Run it where the work happens. Manifest carries the system into the customer's environment, and Catalyst turns what happens next into better data and better models.
Developer Experience
Solution Assembly
Deployment
Execution
Scale
Catalyst Data Engine
Deployment
Solutions are deployed as versioned artifacts through isolated environments and deployment rings, with health checks, approval gates, observability, and rollback controls.
Manifest supports managed SaaS, customer VPC or private cloud, on-premises, air-gapped, and hybrid deployments. Model-provider routing is controlled by the customer configuration; local and air-gapped deployments can operate without sending data to a third-party model provider.
Manifest is subscription software. Teams can configure and operate it directly or use an enterprise deployment supported by MarutAI forward-deployed engineers.
Applied Verticals
MarutAI applies the platform to operations where decisions depend on specialized data, customer-specific models, and tightly governed execution.
Build a system that learns from your operation, improves the models built for it, and expands what your teams can put into autonomous operation.