Prompt Engineering
Low-cost AI trialAnswers whether AI can be used. It is essentially conversational invocation, where capability is bounded by a single input and often remains one-question-one-answer.
InnoGent Platform
An enterprise AI middle platform for agent development, runtime, and operations.
InnoGent provides lifecycle capabilities from data access, knowledge accumulation, and model orchestration to agent deployment and operations. TC Power applies this platform capability to closed-loop automotive R&D testing and validation.
AI Evolution
Enterprise AI is moving from one-off answers to long-running execution. The platform combines application-layer engineering and model adaptation so AI can act correctly, not just sound knowledgeable.
Context Engineering
Make AI understand businessInject industry data and knowledge so AI can support multi-turn context and state. This is the starting point for enterprise applications, but it still mainly assists decisions.
Harness Engineering
Task execution systemUpgrade from conversation to execution. AI gains planning, decomposition, tool use, and action capabilities, replacing parts of manual workflows.
From prompts and context to Harness engineering
Upgrade AI from one-off conversation into long-running task execution with planning, decomposition, tool use, state tracking, and delivery.
SFT + RLHF
Teach models industry language, workflows, and typical judgment patterns, then optimize behavior with human preference feedback.
Platform Overview
TC Power serves closed-loop automotive R&D testing and validation. It integrates goals, business processes, knowledge, data, and tools to decompose, execute, and manage complex engineering work.
External Inputs
Customer needs · Business goals · Enterprise tasks · Management instructions · Industry updates · Intelligence signals
Central Orchestration Agent
Task planning · Resource scheduling · Risk governance
Task decomposition, project management, and phase reporting.
Analysis, research, and information organization work.
Concrete task execution, tool invocation, and result generation.
Enterprise Knowledge And Data Layer
Knowledge bases · Historical projects · Toolchains · Data assets provide shared context for all agents.
Platform Architecture
The three-layer architecture turns one-off capabilities into reusable assets. The platform asset center unifies registration, publishing, permissions, and version management.
Asset Layer
Manage platform assets and accumulate Skills, Flow, and knowledge bases.
Project Layer
Use projects as the core unit, separating asset production from business consumption. Asset projects publish capabilities, while business projects mount and reuse them.
Execution Layer
Turn assets into SOPs, multi-agent orchestration, and retrieval context at runtime to drive agent execution.
Skills: business experience / scriptsFlow: collaboration rules / orchestrationKnowledge base: enterprise knowledge / FAQSOP · Prompt · Runtime tools
Agent Orchestration
Flow orchestration supports long-running multi-agent collaboration. Planner drives global progress, while Generator and Evaluator form the quality loop inside workers.
Planner
Handles planning, decomposition, routing, progress control, checkpoints, scheduled wake-ups, and handoff decisions.
Generator
Produces plans, test cases, scripts, and intermediate artifacts.
Evaluator
Checks quality and objectives, provides improvement feedback, and decides whether to loop back or deliver.
Generator automatically hands off to Evaluator
If the result passes, Evaluator triggers handoff or final delivery. If it fails, it returns improvement feedback and loops back into generation.
Core Modules
TC Power is not just a testing tool. It is a multi-agent infrastructure for enterprise AI digital employees.
Multi-agent orchestration engine
Decomposes complex work into flows, coordinates multi-role agents, and keeps the process controllable and traceable.
Skill co-creation and publishing platform
Turns capabilities into reusable assets for cross-project publishing, reuse, iteration, and co-creation.
Central connector layer
Unifies external system access, standardizes interface capabilities, and builds business closed loops.
Execution runtime system
Provides sandboxed secure execution, automated parallel processing, reproducibility, and traceability.