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USE-Case I

The daily challenge  is the search for evidence, data and logic to progress - experience can only help a little.

Whether you 

  • are tracing why a control flow doesn’t behave as it was designed for, 
  • debugging an interface between a new library and existing components, 
  • or just trying to understand the system well enough to plan the next feature 


you have to 

  • piece it all together yourself across layers and technologies, 
  • cross-referencing runtime behavior with code and configurations, and
  • switching between tools that don't speak to each other. 


Every answer requires building context from scratch. 

 

Needle in the haystack

The daily challenge  is the search for evidence, data and logic to progress - experience can only help a little.

Whether you 

  • are tracing why a control flow doesn’t behave as it was designed for, 
  • debugging an interface between a new library and existing components, 
  • or just trying to understand the system well enough to plan the next feature 


you have to 

  • piece it all together yourself across layers and technologies, 
  • cross-referencing runtime behavior with code and configurations, and
  • switching between tools that don't speak to each other. 


Every answer requires building context from scratch. 

 
 

Needle in the haystack

The daily challenge  is the search for evidence, data and logic to progress - experience can only help a little.

Whether you 

  • are tracing why a control flow doesn’t behave as it was designed for, 
  • debugging an interface between a new library and existing components, 
  • or just trying to understand the system well enough to plan the next feature 


you have to 

  • piece it all together yourself across layers and technologies, 
  • cross-referencing runtime behavior with code and configurations, and
  • switching between tools that don't speak to each other. 


Every answer requires focus and building context in a deliberate, structured, methodical, and controlled way from scratch.

Whether you

  • build a new feature
  • create an issue
  • fix an issue
  • maintain the functionality after an update
  • update libraries
  • extend functionalities for an upgrade the 
  • improve or optimize your components


you have to

  • explore options
  • define requirements
  • analyze the status quo
  • plan the next step
  • design the outcome
  • estimate time and resources
  • prioritize, i.e. allocate time and resources
  • execute the plan
  • implement interface
  • developing code in Python, C++, Rust
  • test your component 
  • validate/verify its functionality in real conditions
  • evaluate the performance
  • review possible changes
 

The way of finding answers

Creating a robot in a deliberate, structured, methodical, and controlled way requires context and focus.

You have to

  • ask questions
  • create assumptions
  • read code
  • trace data and control flows
  • do benchmarks
  • review reports
  • find & identify parameters, relations, correlations or causalities
  • create insights
  • draw conclusions

SMAROBIX Insights engine

Bringing clarity to complexity with agentic engineering to enhance your performance.

  1. Your entire system, captured as a living meta-model — code, config, runtime state across every layer — always there, never stale. No rebuilding (or re-thinking) from scratch every time you sit down.
  2. Work with context-aware, focused information — not abstraction, not less details, but exactly what matters for what you're doing right now.
  3. Use the co-pilot that highlights what matters, lets you explore data and control flows, and resolves issues — automatically or with you in the loop.
  1. We build a holistic meta-model of your robot, incorporating static information from code and configuration, along with runtime information from different levels of your system.
  2. We show you context-aware focused information of your system - not abstraction, not less details - but focused.
  3. Use the agentic co-pilot to highlight and explore your data and control flows and get automated issue resolving or guided assistance.
 

Meta-model-backed approach enhanced by AI.

We understand the benefits of Meta-models and AI. We leverage the strengths of meta-models and AI where they add value, while treating the codebase as the ultimate source of truth.

Preparation of Beta-Release

We ask you to provide us with evidence by answering the question about your setup.

We are currently collecting information about robot engineers' setups in order to provide the useful insights you need and to make sure we cover your set-up.


On one hand, we want to understand how your development set-up looks like. On the other hand, we want to see, how your robot looks like on the hardware as well as on the software side.


Please take some time to fill our survey, you will also be the first, we inform when our software is ready for broader experience.


Register for "INSIGHTS ENGINE" beta

[email protected]

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Whether you

  • build a new feature
  • create an issue
  • fix an issue
  • maintain the functionality after an update
  • update libraries
  • extend functionalities for an upgrade the 
  • improve or optimize your components


you have to

  • explore options
  • define requirements
  • analyze the status quo
  • plan the next step
  • design the outcome
  • estimate time and resources
  • prioritize, i.e. allocate time and resources
  • execute the plan
  • implement interface
  • developing code in Python, C++, Rust
  • test your component 
  • validate/verify its functionality in real conditions
  • evaluate the performance
  • review possible changes


in a deliberate, structured, methodical and controlled way

  • Ask questions
  • Create assumptions
  • Read code
  • Trace data and control flows
  • Do benchmarks
  • Review reports
  • find&identify parameters, relations, correlations or causalities
  • Create insights
  • Draw conclusions


based on evidence, data, logic and experience

BUILT FOR COMPLEXITY.
ENGINEERED FOR CLARITY.
ENHANCED FOR PERFORMANCE.
Built for complexity. Engineered for Clarity. Enhanced for performance.

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