Trusted AI Code Generation
for Embedded Systems
High-success microservice generation, safe deployment, and compliance-ready operations
Traditional embedded AI code generation tries to solve an impossibly large problem in one step: CPU details, peripheral drivers, kernel integration, middleware configuration, application logic, and product-specific wiring. The larger the scope, the higher the risk of hallucinations, brittle revisions, and regressions where a “fix” breaks something unrelated.
Microservice Store takes a different approach. Instead of generating an entire firmware stack, you generate a single, self-contained Microservice, a standalone executable that implements one clear capability. That shift, from “whole product” to “one function”, enables higher success, faster verification, and safer operation in the field.
✨ Smaller Scope, Significantly Higher Success
With Microservice Store, AI focuses on generating one platform-agnostic functionality at a time. The Microservice is pure software, decoupled from CPU and peripheral complexity. This dramatically reduces the search space, making outputs more consistent and lowering the probability of AI hallucinations.
It also changes iteration quality. When the generated artefact is small and modular, revisions remain local. You avoid the classic failure mode of monolithic generation, where each revision reshapes the system and introduces new breakages.
✨ Testable by Design, With Automated Verification
A Microservice is easy to test because it has:
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a clear interface, inputs and outputs
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a limited, well-defined behaviour space
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a single responsibility
That means you can verify it using unit tests, black-box tests, or white-box tests. You can also introduce a second AI agent to generate test cases and unit test code, increasing confidence before deployment.
The result is a more engineering-driven workflow; generation is not the finish line, verification is.
✨ Secure-By-Default Execution; Containment of AI Failures
The most important difference is operational safety.
In monolithic AI-generated firmware, a single malfunction can compromise the entire device because everything runs in one tightly coupled system context. In Microservice Store, AI-generated Microservices run in isolated execution environments. If a Microservice malfunctions or violates expected behaviour, its impact is contained, the runtime can terminate the Microservice independently, and the rest of the device continues operating.
This containment is not only a security improvement but also an operational advantage. Failures become diagnosable events, not catastrophic system incidents.
✨ Authenticated Individual Deployment and Upgrades
AI-generated Microservices are treated as first-class deployable units. They are individually deployable but also individually authenticated during installation, upgrade, and system boot, so only approved Microservices execute on the device.
This means you can safely distribute AI-generated functionality through a governed supply chain, with traceable versions and controlled rollout.
✨ Default-Deny Access; Explicit Permissions with Microservice Access Policy
AI output should never be trusted with unrestricted device access.
By default, an AI-generated Microservice has no access to any device resources, sensitive or non-sensitive, including:
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hardware peripherals
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protected memory regions
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privileged software operations
Access is explicitly granted by the product vendor via the Microservice Access Policy, a protected policy mechanism that defines exactly what the Microservice is allowed to use. Policies are cryptographically protected, so they cannot be tampered with in the field.
This makes AI-generated code safer to adopt, because it is constrained by design, not by hope.
✨ Custom, Optimised Microservices Instead of heavyweight Libraries
Many embedded libraries are powerful, but they come with large configuration surfaces and complex dependency graphs. This creates an unmanageable test matrix and unnecessary resource overhead, especially when you need only a single, narrow function.
With Microservice-based AI generation, you can generate highly optimised, product-specific Microservices with minimal configuration and minimal overhead.
For example, instead of integrating a full cryptography library with many unused features and options, you can generate a single-path a crypto no-configure algorothm.
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