Native Engines
Native Engines are the foundational, always-on subsystems that power every workflow, intelligence module, automation, and integration executed within ChordianAI. They represent the platform’s internal operating system — a collection of deeply integrated capabilities that enable ChordianAI to understand, orchestrate, execute, and optimize enterprise tasks at scale.
Native Engines provide:
- Semantic understanding
- Workflow reasoning
- Data transformation
- Secure integration
- Compute optimization
- Reliable orchestration
- Full audit and governance
These are not features users purchase individually; they are the computational substrate that makes ChordianAI possible.
Engine Catalog
| Engine | Status | Description | Example Use Cases |
|---|---|---|---|
| AI Problem Analyzer | Active | Translates natural-language business objectives into executable workflows | ”Optimize energy spend,” “Detect churn risk,” “Plan maintenance” |
| Workflow Builder | Active | No-code visual canvas for designing, connecting, and configuring agents and data flows | Build forecasting or optimization workflows manually |
| Workflow Orchestrator | Active | Executes workflows across compute environments (CPU, GPU, cloud, hybrid) | Multi-model execution with unified logging and retry logic |
| Workflow Analyzer | Request access | Detects inefficiencies, redundancy, or missing connections in workflows | Workflow weak spots audit, cost and runtime optimization |
| Data Cleaner | Request access | Performs data quality checks, normalization, and preprocessing | Prepare sensor or financial datasets |
| Data Connector | Request access | Integrates with AWS, Azure, Snowflake, SAP, Salesforce, and SQL | Live data ingestion from enterprise sources |
| Output Agent | Active | Exports results to dashboards, APIs, files, or communication tools | Send Excel reports, push results to Slack or PowerBI |
AI Problem Analyzer
Status: Active | Function Class: Cognitive Parsing & Workflow Synthesis
The AI Problem Analyzer receives abstract business objectives, operational requests, or strategic directives formulated in natural language and transforms them into formalized workflow specifications composed of ChordianAI agents. It performs advanced semantic decomposition, identifies required computational tasks, determines dependencies, and constructs the minimal viable workflow graph.
Inputs & Outputs
| Inputs | Outputs |
|---|---|
| Natural-language business directives | Workflow DAG composed of ChordianAI agents |
| Semi-structured operational instructions | Formal problem specification and task classification |
| Historical workflows and system context | Required inputs and data dependencies |
| Organizational metadata | Constraint and KPI extraction |
| Domain constraints | Execution pre-conditions and validation rules |
Workflow Builder
Status: Active | Function Class: Workflow Authoring & Configuration
The Workflow Builder is ChordianAI’s visual composition environment for constructing and modifying workflow structures. It provides a controlled interface for assembling agents, defining execution logic, configuring inter-agent data flows, and embedding conditional or parallel behavior.
The Builder enforces structural correctness, parameter consistency, data dependency coherence, and compliance with enterprise guardrails.
Workflow Orchestrator
Status: Active | Function Class: Execution Engine & Runtime Governance
The Workflow Orchestrator is the runtime backbone of ChordianAI. It executes workflows across hybrid compute environments with strict adherence to enterprise governance, safety controls, and performance requirements.
It manages:
- Scheduling and sequencing of agents
- Parallel and conditional execution
- Cost-aware model routing
- Enforcement of guardrails and policies
- Human-in-loop checkpoints
- Fallback mechanisms and recovery logic
- Real-time event-driven execution
- Comprehensive auditing and observability