Data & AI Agentic AI

AI‑assisted ECU development and validation

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InDe.ai
AI‑assisted ECU development and validation

InDe.ai is an AI engineering ecosystem for ECU development, validation, and metrics for management in ECU software development. InDe.ai connects agentic AI with real and virtual ECUs to support faster and more reliable engineering decisions across the automotive V‑cycle. Developed by Diconium India and its subsidiary Embitel Technologies.

What InDe.ai is designed for

ECU development teams are under pressure: growing software complexity, fragmented toolchains, limited hardware access, and rising validation demands. InDe.ai addresses these challenges by bringing AI‑assisted engineering intelligence and real execution together in one controlled environment. Instead of moving between disconnected tools and manual workflows, teams work within a unified ecosystem that supports development, validation, and feedback as a continuous process.

A unified engineering ecosystem

InDe.ai brings multiple AI‑assisted engineering applications together in a single, application‑centric platform.

At its core is an agentic AI system that works hand in hand with a Smart ECU Farm. The AI‑based applications cover requirements generation, design, coding, test cases, and testing. As part of embedded software development, AI agents retrieve relevant engineering knowledge, coordinate workflows, and trigger execution on real and virtual ECUs when required.

All components run on‑premises, ensuring full control over data, models, and execution workflows. This enables execution‑aware AI support without relying on public cloud environments. The system can also be configured to use external environments if required by the development setup.

InDe.ai connects AI‑assisted engineering applications, middleware, and execution infrastructure in a single on‑premises ecosystem.

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Supporting the automotive V cycle end to end

InDe.ai is built to support ECU development and validation as a continuous loop rather than isolated phases. This supports agile software development by enabling seamless transitions between development and testing. AI assistance is present across all stages of the development cycle and is fully integrated. Requirements can be analyzed and improved early, code can be reviewed and documented with AI assistance, and tests can be generated and executed directly on real and virtual ECUs. Logs, defects, and runtime data are continuously linked back to requirements and code, enabling informed engineering decisions throughout the V cycle. InDe.ai supports development, validation, and feedback across the automotive V cycle.

InDe.ai supports development, validation, and feedback across the automotive V‑cycle.

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Core capabilities at a glance

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Engineering intelligence

InDe.ai supports requirements analysis, code analysis, documentation with AI assistance, log analysis, defect analysis, hardware integration, and CI/CD workflows, helping teams identify gaps, conflicts, and issues early in the development process.

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Development and test execution

Integrated development environments, automated test generation, and direct execution on real and virtual ECUs reduce manual effort and accelerate validation cycles.

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Observability and feedback

Execution data, logs, and defects are analyzed and connected across stages, creating transparency and continuous feedback between development and validation.

Engineering impact

InDe.ai is designed to support measurable improvements in ECU development and validation:

  • Reduced manual effort through AI‑assisted orchestration
  • Earlier validation on real and virtual ECUs
  • Continuous feedback based on execution data
  • Human‑in‑the‑loop AI with reviewable outputs
  • Intuitive UI and UX, with many operations supported through drag‑and‑drop interactions
  • Secure and governed operation through on‑premises deployment

Built for software‑defined vehicles

  • InDe.ai scales across teams and programs and supports the growing complexity of software‑defined vehicle architectures.

  • It enables AI‑assisted engineering without compromising security, governance, or execution fidelity.

Talk to our experts

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In this session, we review your current setup and discuss where AI‑assisted execution and validation can create tangible engineering impact.

FAQ

What is InDe.ai?

InDe.ai is a private, on premises AI engineering ecosystem for ECU development and validation. It combines agentic AI with real and virtual ECU execution to support development, verification, and validation across the automotive V cycle within a single, unified environment. It is also an application centric, API based platform that enables the implementation of additional AI based engineering applications.

Which engineering challenges does InDe.ai address?

InDe.ai is designed for ECU development teams dealing with fragmented toolchains, manual effort across requirements and testing, limited access to hardware, late detection of integration and quality issues, and strict requirements for data security and IP protection. By connecting AI assisted analysis directly with execution on real and virtual ECUs, the platform reduces handovers and delays across development and validation.

How does InDe.ai use AI in ECU development? 

InDe.ai uses a retrieval‑augmented, agentic AI system with locally hosted language models. Instead of relying solely on pretrained data, the agents retrieve relevant engineering information from connected data sources and applications. These agents coordinate workflows such as requirements analysis, code analysis, test generation, execution, and result aggregation while keeping engineers in control at every step. 

What is the Smart ECU Farm? 

The Smart ECU Farm is the execution layer of InDe.ai. It consists of physical test benches with real ECUs, complemented by virtual components and on‑demand virtual machines. When execution is required, AI agents securely trigger workflows to flash software, run test cases and scripts, and collect runtime data from real and virtual hardware. 

How are test cases and test scripts handled? 

InDe.ai supports the automated generation of test cases and test scripts, including the conversion of manual tests into automation. Generated test scripts can be deployed directly to the Smart ECU Farm for execution and integrated into existing CI/CD pipelines to support continuous validation. 

Is InDe.ai deployed in the cloud or on‑premises? 

InDe.ai is deployed fully on‑premises. Language models, AI inference, compute infrastructure, and data storage run on local CPU and GPU servers. This ensures full control over data, models, and execution workflows. Cloud integration is possible if specific project requirements require it. 

Does InDe.ai operate autonomously or replace engineers? 

No. InDe.ai follows a human‑in‑the‑loop approach. While the platform automates repetitive and compute‑intensive tasks, engineers remain responsible for reviewing and approving AI‑generated outputs 

Who is InDe.ai intended for? 

InDe.ai is intended for automotive organizations developing software‑defined vehicles, particularly teams responsible for ECU development and validation that require secure AI capabilities, controlled execution on real hardware, and scalable support across programs and teams.