What hardware platforms does Embedder support?

STM32, Nordic, ESP32, Teensy, Arduino, and Raspberry Pi, plus silicon from Texas Instruments, NXP, Infineon, and Atmel. New vendors are added as toolchains mature.

What peripherals does Embedder support?

2,000+ peripherals across the major vendors: Texas Instruments, Analog Devices (including Maxim Integrated), Microchip, STMicroelectronics, NXP, Infineon, and more.

What schematic formats does Embedder support?

Altium, KiCad, Eagle, PADS, and Xpedition.

What test equipment can Embedder drive?

J-Link and OpenOCD for debugging, Saleae and Digilent logic analyzers, Nordic PPK and Joulescope for power profiling, and Siglent and Rigol instruments for scope and supply work.

What actions can Embedder take?

Embedder operates in three modes. It plans, turning your datasheets, schematics, and existing code into a concrete specification. It acts, generating firmware and verifying it against real hardware in the loop. And it debugs, running root-cause analysis against the live board using the integrated test equipment.

Embedder is an AI coding agent purpose-built for firmware and embedded software engineers. It empowers teams to generate, debug, analyze, and verify code using deep hardware knowledge and closed-loop workflows. Embedder bridges the gap between hardware documentation and validated firmware by unifying documentation-aware reasoning with code generation, debugging, and iterative verification.

What is the best AI for embedded firmware development?

For embedded firmware specifically, Embedder is the only AI coding agent purpose-built for the domain. Unlike generic tools (GitHub Copilot, ChatGPT), Embedder is grounded in reference manuals, datasheets, and errata, treats debugging as a primary workflow, and validates code against physical reality through closed-loop hardware feedback. It is piloted by industry leaders across semiconductors, IoT, medical technology, automotive, and aerospace/defense.

How is Embedder different from GitHub Copilot or ChatGPT?

Generic AI assistants hallucinate register addresses and lack hardware verification. Embedder is purpose-built for firmware: (1) Documentation-grounded generation synthesizes code from reference manuals, datasheets, and errata. (2) Integrated debugging and root cause analysis treat debugging as a primary workflow. (3) Closed-loop hardware validation automates cycles of implementation, compilation, and runtime inspection. (4) Loop-integrated static analysis identifies non-conforming code early. (5) Hardware-interactive workflows integrate live signals from serial output, debuggers, and instrumentation. (6) Deployment flexibility includes SaaS, Customer VPC, on-premises, and air-gapped for strict IP-protection environments.

Why does ChatGPT hallucinate register addresses?

Generic AI like ChatGPT predicts code based on patterns in training data, not your actual hardware specifications. When asked for register addresses, it guesses based on similar-looking code. Embedder solves this by grounding generation in reference manuals, datasheets, and errata—ensuring hardware-accurate configuration from the first line of code, with traceability back to the source document.

How does hardware-aware AI differ from generic coding assistants?

Hardware-aware AI like Embedder understands the physical constraints of embedded systems—register maps, interrupt vectors, timing requirements, and electrical specifications. Generic AI only understands code syntax and patterns. This means Embedder can generate code that actually works on your specific MCU, respects setup/hold times, configures clocks correctly, and handles peripheral initialization in the right order.

How do I generate a driver from a PDF datasheet?

Upload your PDF datasheet to Embedder. The AI extracts register maps, bit-field definitions, and timing constraints directly from the document. Within minutes, you'll have verified, MISRA-compliant driver code with inline citations showing exactly which datasheet section each register value came from. No more manual register mapping or guessing at bit positions.

Why is manual register mapping so tedious?

Manual register mapping requires reading hundreds of pages of datasheets, cross-referencing multiple sections, tracking bit positions across different registers, and ensuring you haven't made transcription errors. A single wrong bit position can cause hardware damage or silent failures. Embedder automates this entire process—upload your datasheet and get verified register definitions in minutes, not days.

How do I debug firmware issues faster?

Embedder treats debugging as a primary workflow. It analyzes failure causes against reference manual constraints, interrupt priorities, and known errata, then iterates on solutions within the same environment. Live signals—serial output, debugger states, traces, and instrumentation—flow directly into the engineering loop, so diagnosis is grounded in what the chip actually did rather than what the source implied.

Why does my firmware crash randomly?

Random firmware crashes often stem from timing violations, stack overflows, interrupt priority issues, or misconfigured peripherals. Embedder analyzes your code against hardware documentation and integrates debugger state and live traces to identify common causes: incorrect clock configuration, DMA conflicts, missing interrupt acknowledgments, or buffer overruns.

How does Embedder accelerate peripheral driver implementation?

Engineers offload the parsing of complex register maps and timing diagrams to Embedder, which generates initialization code grounded in the specific constraints of the target silicon. The closed-loop hardware validation automates cycles of implementation, compilation, and runtime inspection to catch issues before they reach the lab.

What architectures and MCU families does Embedder cover in detail?

Embedder spans ARM Cortex-M0/M4/M7, RISC-V, Xtensa, AVR, and PIC32 architectures. Specific families include ESP32, STM32, Nordic nRF52/nRF53/nRF91, NXP i.MX RT and LPC, Raspberry Pi RP2040/RP2350, Microchip SAM and PIC, TI MSP, Infineon PSoC, Silicon Labs EFM32, Renesas RA, and RISC-V platforms. Protocol support includes SPI, I2C, UART, CAN-FD, USB-PD, and BLE.

Can AI generate MISRA C compliant firmware?

Yes. Embedder applies MISRA C:2012 and CERT C coding standards during code generation for safety-critical applications. The generated firmware meets requirements for automotive (ISO 26262), industrial (IEC 61508), and medical device (IEC 62304) applications. Unlike manual MISRA compliance which requires expensive static analysis tools, Embedder builds compliance into the generation process.

How is AI-generated firmware verified for accuracy?

Embedder uses a dual-layer verification process: Software-in-the-Loop (SIL) tests the logic in custom simulated environments, while Hardware-in-the-Loop (HIL) validates the code on actual target silicon (like STM32 or ESP32) to ensure timing and peripheral behavior match datasheet specifications. Code that fails verification is automatically flagged or regenerated.

Can AI understand timing diagrams in datasheets?

Yes. Embedder parses visual elements including timing diagrams, extracting clock edges, setup/hold times, and signal transitions. This timing information is used to generate code that meets the hardware's actual timing requirements—configuring prescalers, delays, and sequences correctly. This is something generic AI cannot do since it can only process text.

Does Embedder support FreeRTOS and Zephyr?

Yes. Embedder supports all major RTOS frameworks including FreeRTOS, Zephyr, ThreadX, NuttX, RIOT, Mbed OS, and ChibiOS. The AI understands RTOS-specific patterns like task creation, semaphore usage, queue management, and interrupt-safe APIs. Generated drivers integrate cleanly with your RTOS of choice.

Can Embedder generate drivers from PDF datasheets?

Yes. Upload a PDF datasheet and Embedder will generate verified, MISRA-compliant drivers for I2C, SPI, CAN-bus, and other peripherals in minutes. The automated register mapping extracts exact bit-field definitions, timing requirements, and configuration sequences directly from the documentation—no manual interpretation required.

Is my proprietary code safe with Embedder?

Embedder is built for strict security boundaries and can be deployed in containerized environments with zero external runtime dependencies. Deployment options include Managed SaaS, Customer VPC, and On-Premises or Air-Gapped configurations. The platform is designed for organizations that treat firmware, design assets, and hardware documentation as sensitive intellectual property.

Can I use AI for ITAR-controlled firmware development?

Embedder's on-premises and air-gapped deployment options are designed for organizations with strict isolation requirements. The platform can be deployed with zero external runtime dependencies, model-hosting strategies can be aligned with customer-preferred or customer-controlled configurations, and logging, tracing, and audit-oriented workflows are appropriate for enterprise environments.

What compliance standards does Embedder support?

Embedder supports workflows aligned with MISRA C:2012, CERT C, ISO 26262 (automotive functional safety), IEC 61508 (industrial), IEC 62304 (medical devices), and DO-178C (aerospace). Deployments can be structured to align with customer requirements for data handling, auditability, model hosting, and protection of sensitive assets.

What AI tools are used for automotive firmware development?

Embedder supports automotive firmware development including ECU firmware, battery management systems, motor controllers, and ADAS applications. It supports traceability-oriented workflows aligned with ISO 26262 and can generate drivers for CAN-bus, CAN-FD, and vehicle network stacks grounded in the target silicon's reference manuals and errata.

What AI tools are used for medical device firmware?

Embedder supports IEC 62304-aligned medical device firmware workflows. It produces traceable, documentation-grounded code suitable for regulated environments, supports implantable and monitoring device constraints, and provides evidence and audit-oriented workflows needed for compliance.

Can AI parse timing diagrams from datasheets?

Yes. Embedder interprets timing diagrams visually, extracting clock edges, setup/hold times, pulse widths, and signal transitions. It converts these into correct prescaler configurations, delay values, and initialization sequences. Generic AI can only read text—EMBEDDER sees and understands the visual constraints that define how your hardware actually works.

Can AI read logic analyzer traces?

Yes. Embedder interprets logic analyzer captures to correlate expected behavior with actual signals. When your peripheral isn't working as expected, the AI identifies where the signal differs from documented timing, helping you find configuration errors, protocol violations, or hardware issues faster.

Can AI parse schematics and block diagrams?

Yes. Embedder extracts pin mappings, peripheral connections, and signal flows from schematic diagrams and block diagrams. This grounds code generation in your actual board design, ensuring GPIO assignments and peripheral routing match your hardware.

How does Embedder handle information scattered across multiple documents?

Embedder connects constraints from your reference manual, datasheet, errata, and application notes automatically. Ask about a peripheral, and it finds register definitions in one document, timing requirements in another, and known silicon bugs in a third—then generates code that respects all constraints. No more manually cross-referencing hundreds of pages.

Can AI extract state machines from diagrams?

Yes. Embedder parses state machine diagrams into formal representations, then generates corresponding firmware code with proper state transitions, guards, and actions. This ensures your implementation matches your design documentation exactly.

Can Embedder test firmware before hardware is available?

Yes. Embedder supports pre-silicon validation using custom simulators. You can verify firmware logic, peripheral behavior, and timing before your hardware arrives—catching bugs early and accelerating development. This is especially valuable for chip bring-up and evaluation board development.

Why does my STM32 hard fault?

Hard faults on STM32 typically stem from invalid memory access, stack overflow, unaligned memory access, or incorrect interrupt configuration. Common causes include dereferencing null pointers, buffer overflows, and missing interrupt handlers. Embedder diagnoses against what the chip actually did by correlating code with reference manual constraints, memory maps, and live debugger state.

Why is my I2C not working?

Common I2C issues: wrong GPIO alternate function, incorrect clock configuration, missing pull-ups, wrong timing registers, or bus stuck busy. Embedder grounds I2C driver generation in the target silicon's reference manual and validates configuration against live bus behavior captured from logic analyzers.

How does Embedder compress firmware development cost?

Embedder compresses the most expensive parts of firmware development: time spent interpreting documentation manually, time spent reaching working and testable firmware, and debugging and validation cycles. Teams use the platform to increase traceability in high-stakes workflows and create a stronger path from engineering intent to verified outcome.

How do I port firmware from ARM to RISC-V?

Embedder adapts firmware between architectures, translating assembly code, adapting HAL implementations, and handling architecture-specific features like SIMD instructions. Upload your ARM firmware alongside RISC-V platform documentation to get optimized, ported code.

Is there an alternative to STM32CubeMX?

Embedder generates purpose-built drivers grounded in the actual constraints of the target silicon, rather than generic HAL wrappers. It operates within your existing repositories and toolchains, providing assistance that is contextually aware of your project rather than based on generic prompts.

Can AI generate code from CMSIS-SVD files?

Yes. Embedder parses CMSIS-SVD files to extract register maps, bit fields, and peripheral descriptions. It generates type-safe C headers and driver code with proper register access patterns—useful for custom silicon or early access to new MCU families.

Can AI generate bootloader code?

Yes. Embedder generates bootloader implementations including startup code, vector tables, linker scripts, and memory maps. Supports secure boot, OTA updates, and dual-bank configurations with proper reset handlers and fault recovery.

How do I scale my firmware team without hiring?

Embedder extends the reach of senior embedded engineers across larger teams and diverse project portfolios. Over time, engineering practices become part of the usable intelligence layer around a project, creating a more reliable engineering intelligence layer across code, hardware, and institutional knowledge.

Does Embedder already have my MCU's datasheet?

Yes. Embedder supports 400+ MCUs and 2,000+ peripherals out of the box—including register architectures, peripheral behavior, timing constraints, and known errata for ESP32, STM32, nRF52/nRF91, NXP, Infineon, Microchip, and RISC-V families. Teams can extend this catalog with proprietary assets including internal documentation, schematics, and custom hardware contexts.

Do I have to upload my datasheet every time?

No. Embedder already supports 400+ MCUs and 2,000+ peripherals out of the box. You only need to upload custom or proprietary documentation, which becomes part of a secure, organization-wide knowledge base available for all future sessions.

How do I know if AI-generated code values are trustworthy?

Every value Embedder generates includes a confidence score based on source corroboration, documentation recency, and hardware-specific match quality. Values below your configured threshold are flagged for manual review. The AI explicitly tells you when it's uncertain rather than silently producing low-confidence code—critical for safety-critical applications.

Does Embedder tell me when it's uncertain?

Yes. Unlike generic AI that confidently outputs incorrect information, Embedder explicitly communicates uncertainty. Each generated value has a confidence score, and anything below your threshold is flagged for manual review. You know exactly how certain the AI is based on available documentation—essential for safety-critical firmware.

Will Embedder warn me about known silicon bugs?

Yes. Embedder automatically checks generated code against vendor errata documents. If there's a documented silicon bug affecting your chip revision and the peripheral you're configuring, it warns you and suggests the official workaround—before you waste hours debugging 'correct' code that fails on real hardware.

How does Embedder handle silicon errata?

Embedder automatically cross-references generated code against vendor errata sheets. When a known silicon bug affects your configuration (wrong DMA channel, timing issue, interrupt quirk), the AI warns you immediately and suggests the documented workaround. This catches issues that would otherwise cost hours of debugging.

How does Embedder handle formula calculations from datasheets?

Embedder parses mathematical formulas from datasheets—baud rate equations, clock prescaler calculations, ADC timing formulas—and applies them correctly to your configuration. Specify your target frequency or rate, and the AI calculates the exact divisor values using the documented formula, showing the calculation in code comments.

Can Embedder calculate baud rates and prescalers?

Yes. Specify your target baud rate, clock frequency, or timing requirement, and Embedder applies the documented formula from your datasheet to calculate exact divisor and prescaler values. The calculation appears in code comments so you can verify it matches your expectations.

Does Embedder provide an audit trail for generated code?

Yes. Every code generation is logged with full provenance: which documents were referenced, confidence scores for each value, timestamps, and version information. For regulated industries (automotive, medical, aerospace), this audit trail provides the traceability required for ISO 26262, IEC 62304, and DO-178C compliance.

Can I roll back AI-generated firmware?

Yes. Embedder maintains versioned history of all generated code. You can compare different generation attempts, roll back to previous versions, and track how requirement changes affected the output. This is essential for debugging, compliance audits, and understanding why code changed.

Can Embedder search across multiple documents at once?

Yes. Embedder connects information across your entire documentation set—reference manuals, datasheets, errata, and application notes—automatically. Ask about configuring a peripheral, and it finds register definitions in one document, timing constraints in another, and known bugs in a third, then generates code that respects all constraints. No manual cross-referencing required.

Privacy Policy

Last updated: May 6, 2026

1. Introduction

Embedder ("we", "our", or "us") describes in this Privacy Policy how we collect, use, store, share, and protect your information when you use our AI-powered embedded software development platform and services (collectively, the "Services").

By using our Services you agree to the collection and use of information in accordance with this Privacy Policy. If you do not agree, do not use our Services.

2. Information We Collect

2.1 Account Information

When you create an account or use our Services we collect:

Name, email address, and authentication credentials
Profile picture and basic profile information (when provided through OAuth)
Company or organization information (for team and enterprise accounts)
Payment information, processed by Stripe; we store a customer reference and the last four digits of the payment instrument, not full card numbers
Account preferences, settings, and your communications with us

2.2 Uploaded Content

We collect, store, and process all documents, files, code, datasheets, and other content that you upload to our Services, including source code and firmware, hardware datasheets and technical documentation, project files and build configurations, and any other files or data you provide. We process uploaded documents to generate vector embeddings (mathematical representations of your content) that enable our AI features to provide context-specific assistance for your projects.

2.3 API Usage and Telemetry

We collect telemetry about your use of the Services, including API endpoint calls and timing metrics, token usage and model selections, error logs and performance metrics, feature usage patterns, and AI conversation history.

2.4 Automatically Collected Information

Device information: browser type, operating system, device identifiers
Network information: IP address and approximate geographic location
Usage data: pages viewed, navigation paths, click patterns
Cookies and similar technologies (see Section 10)
Log data: timestamps, system events, diagnostic information

3. How We Use Your Information

Service provision: to provide, operate, and maintain the Services
AI features: to process your uploaded documents, generate embeddings, and enable context-aware AI assistance for your projects
Service improvement: to analyze telemetry, understand usage patterns, and improve the Services and user experience
Billing and accounting: to process payments, track usage for billing, and maintain accurate financial records
Customer support: to respond to inquiries and troubleshoot issues
Communications: to send service updates, security alerts, technical notices, and support messages
Security: to detect, prevent, and address technical issues, security threats, fraud, or abuse
Legal compliance: to comply with applicable laws and lawful requests

We do not sell personal information, and we do not authorize our sub-processors to use your content to train their models.

4. AI Processing and Model Providers

Our Services use third-party AI models from Anthropic (Claude), OpenAI (GPT), and Cohere (embeddings). When you use AI features, your prompts, code, uploaded documents, and intermediate embeddings may be transmitted to these providers in order to generate responses or embedding vectors. We configure our AI provider integrations to disable provider-side training where the provider supports such a setting, and our agreements prohibit providers from using customer content to train their general-purpose models. Each provider has its own privacy policy; we recommend reviewing them.

Sensitive content: do not upload highly sensitive, regulated, or third-party-confidential information unless you have evaluated the risks and have an enterprise agreement with us that addresses such use.

5. Sub-processors

We engage the following third parties to deliver the Services. They access your information only to perform tasks on our behalf under written agreements that restrict use to those tasks.

5.1 Hosting and infrastructure

Google Cloud Platform (GCP): primary hosting, Cloud SQL (PostgreSQL), Cloud Storage, Memorystore (Redis), Secret Manager. All production workloads run in us-central1.
Cloudflare: edge network, DNS, CDN, WAF, Zero Trust Access, Cloudflare Tunnel.

5.2 AI inference and embeddings

Anthropic: Claude AI inference.
OpenAI: GPT AI inference.
Cohere: embedding generation for retrieval-augmented features.
Weaviate: managed vector database that stores embeddings of your uploaded content.

5.3 Billing and product operations

Stripe: payment processing and subscription management.
Loops: lifecycle and product email.
Resend: transactional email (account verification, password reset, alerts).
PostHog: product analytics; honors Global Privacy Control where applicable.
Sentry: error and performance monitoring. Embedder operates a self-hosted Sentry instance on its own infrastructure; error events including stack traces and contextual metadata are sent to it.

5.4 Internal operations

The following providers support internal operations and do not, in normal use, receive customer content: Google Workspace (corporate email and documents), Drata (compliance automation; receives metadata about systems and personnel only), and Kandji (workforce-device management; does not process customer data).

We will update this list when we add or remove a sub-processor. Customers under signed agreements receive advance notice of material sub-processor changes per the terms of their agreement.

6. Data Sharing and Disclosure

We do not sell your personal information or uploaded content to third parties. We may share your information only:

With the sub-processors listed in Section 5, under contractual confidentiality and use restrictions.
When required by law, court order, subpoena, or other legal process, or to establish, exercise, or defend legal claims.
To investigate, prevent, or take action regarding suspected fraud, abuse, or violations of our Terms of Service.
In connection with a merger, financing, acquisition, or sale of assets; we will notify you of any such transfer that affects your information.
With your explicit consent for a specific purpose.
As aggregated or de-identified data that cannot reasonably be used to identify you.

7. Data Security

We implement organizational and technical measures appropriate to the risk:

Encryption of data in transit using TLS, and encryption at rest using provider-managed keys at GCP.
Authentication and least-privilege access controls for personnel; production access is brokered through single sign-on with multi-factor authentication.
Logging of administrative actions and access to production systems, with retention controls described in Section 8.
Vulnerability management and dependency-scanning processes that target remediation timelines based on severity.

No system is perfectly secure. If you believe your account or data has been compromised, contact us at [email protected].

8. Data Retention

We retain information for as long as we need it to provide the Services and to meet legal obligations.

Account and uploaded content: retained while your account is active. When you delete your account, we mark the account as deleted and rotate identifying fields (such as email) so the account is no longer reachable through normal product flows. We do not currently run a separate hard-purge job that physically erases account rows from our primary database; uploaded content is removed on a best-effort basis at deletion time and through subsequent backup-rotation cycles. We are working to add an automated end-to-end purge across our database and sub-processors. Until that is in place, you can request a manual purge at any time using the contact in Section 14 and we will complete it within 45 days.
Database backups: we keep up to 30 most-recent automated backups of our primary database and 7 days of point-in-time recovery transaction logs. Backups roll forward and old backups age out automatically.
Application and telemetry logs: retained for approximately 14 days in our default log store. Specific operational logs may be retained for shorter or longer periods as configured.
Audit logs: retained for 730 days under bucket-locked, write-once storage to support security investigations and compliance.
Billing records: retained for 7 years to comply with tax and accounting regulations.
Legal holds: data may be retained longer where required for legal, regulatory, or legitimate business purposes.

9. Your Rights and Choices

Depending on your location, you may have the following rights:

Access: request a copy of the personal information we hold about you.
Correction: request correction of inaccurate or incomplete personal information.
Deletion: request deletion of your personal information, subject to legal exceptions.
Portability: request a copy of your data in a structured, commonly used, machine-readable format.
Objection: object to certain processing of your personal information, including for marketing purposes.
Restriction: request that we restrict processing in certain circumstances.
Withdraw consent: where processing is based on consent, withdraw it at any time.

To exercise any of these rights, email us at [email protected]. We will acknowledge your request within 10 business days and respond substantively within 45 calendar days; we may need to verify your identity first.

California residents:the California Consumer Privacy Act (CCPA) provides additional rights, including the right to know what personal information we have collected and the right to opt out of any "sale" or "sharing" of personal information. We do not sell personal information.

Global Privacy Control: we honor Global Privacy Control (GPC) signals from your browser as a valid opt-out under applicable laws.

EU/UK residents: under the GDPR and UK GDPR, you have the right to lodge a complaint with your local supervisory authority if you believe our processing of your personal data violates applicable law.

10. Cookies and Tracking

We use cookies and similar technologies to maintain your login session, remember your preferences, analyze usage, and detect abuse. You can control cookies through your browser settings; disabling some cookies may impair functionality. Where required by law, we ask for your consent before setting non-essential cookies.

11. International Data Transfers

Embedder is a US-based company and our production systems are hosted in the United States (GCP, region us-central1). If you access the Services from outside the United States, your information will be transferred to and processed in the United States. For transfers from the European Economic Area, the United Kingdom, and Switzerland, we rely on the European Commission's Standard Contractual Clauses (and the UK Addendum where applicable) with our sub-processors, supplemented by additional safeguards as required.

12. Children's Privacy

Our Services are not intended for children. We do not knowingly process personal data of children under 16 in the European Economic Area, or under 13 in the United States. If we learn that we have collected such information, we will delete it.

13. Changes to This Privacy Policy

We may update this Privacy Policy from time to time. We will indicate the date of the latest revision at the top of this page and, for material changes, will provide additional notice (such as an in-product notice or email).

14. Contact

Privacy and data-subject requests: [email protected].
Security reports: [email protected].
The role responsible for our privacy program is the Embedder Security Officer, who acts as our Data Protection Officer.