Controls development, end to end
DAI-SE is for controls development broadly, and systems engineering is one part of it. Teams use it to produce the engineering artifacts their programs depend on.
What this video demonstrates
The film has no narration. It carries its message in on-screen captions and music. This is that text, in order.
Opening. From LHP Engineering Solutions. DAI-SE. Digital AI Specialized Engineer. 25+ years of LHP safety-engineering work, calibrated into a validated skills library, and the platform that runs it. Engineering for safety-critical vehicle systems.
The program. 400 volts. 96 cells in series. Software between them and a fire. The customer's ask is the BMS application software. Not the hardware, which is sourced separately. This is how that software gets engineered.
Stage 1. Definition. A new program. The customer's statement of work is the starting point. DAI-SE loads LHP's validated skills for the stage: ISO 26262 item definition, interface control, system context. It plans before it writes, and sets an eleven-point pass bar for itself. It reads the statement of work. Program, customer, software scope. Nothing invented. Where the customer has not decided, it does not guess. It writes the decision they have to make. The item boundary. Every interface. Every external dependency.
Stage 2. Decomposition. The system decomposed into functions: state determination, battery control, fault management. Change it on the fly, in plain language. It edits the model, not a picture. Another layer of subfunctions. Seconds, not another workshop.
Requirements. Author the system requirement specification. Then 226 system requirements, each one traced back to the element it came from.
Stage 3. Architecture. System architecture. Every interface the customer has not specified is marked TBD, not invented. Then the software design: 26 components across four layers. Hardware abstraction, basic software, application, safety supervisor. Operating modes as a state machine: precharge, propulsion, charging, degraded, fault shutdown. Same architecture, now as models. A SysML v2 structure model and an OPM conceptual model, both from the same source. Software requirements. A verification test specification, each test linked to the requirement it verifies.
The gate review. Sixteen artifacts, filed by lifecycle stage, every one traceable. Then the review. Ask it whether the work is ready to move. It reads the whole project against the gate criteria. Example finding: first software delivery is due the same week as the requirements review, six weeks before the architecture review. Acceptance is the agreed test suite. There is no test suite. Gate recommendation: Hold. Six gates. Six holds. Every one cited to a clause.
Into the ALM. And it lands where the program lives: your ALM. Here that is Jama. The same mapping works for any tool with item types and trace links. It reads the ALM's item types and proposes the mapping, with its reasoning for each rule. Then it pushes: every requirement as its own item. 226 requirements in the ALM. Individual items. Trace links intact.
Into the development toolchain. DAI-SE is also an MCP server. Point any agent harness at it, GitHub Copilot, Claude Code, Codex, and it gets LHP's validated skills library and the program's artifacts. Connect the skills library to your repository. Link Jira so stories flow back. Assign a story to a coding agent. Through MCP it picks up the skills, the requirements, the interface spec and the test cases it needs, and develops against them. The pull request cites the requirements it implements, the interface it honors and the tests that verify it, traced back to the story in Jira.
Close. One session. Sixteen artifacts. 226 traced requirements in your ALM. And an honest list of what is still open.
16artifacts in one demo session
226system requirements, each traced
6gates reviewed, every hold cited
25years of LHP safety engineering
One session, on a battery management system program, from the customer's statement of work to requirements in Jama.
Who DAI-SE is for
Engineering executives who want better AI adoption at scale for controls development, but are struggling to keep quality and consistency from general-purpose LLMs across their users.
Less time spent prompting
LHP's skills and your own process are already in the platform, so engineers spend their time reviewing and deciding instead of rewriting prompts to coax a usable draft out of a general-purpose assistant.
The same quality from every engineer
Everyone on the team draws on the same validated skills and workflows, so the output does not depend on who wrote the prompt.
Three things a general-purpose AI assistant does not have
DAI-SE is specialized in three ways, and the combination is what gets an engineer to a usable first draft inside a governed workflow.
LHP's skills library
25+ years of LHP engineering practice and high-quality engineering data, packaged as validated skills and layered on top of general-purpose LLMs. Each skill carries a status, so a project only draws on skills that have been validated. DAI-SE starts out trained the LHP way, not as a generalist.
Your data, frameworks and expertise
Add your own process documents, engineering data and subject matter expert knowledge in a structured way, and skills can be created from them. DAI-SE then produces outputs the way your organization already produces them, in the formats your teams already use.
A governed engineering framework
DAI-SE connects to common engineering toolchains such as ALMs, source code management systems, and modeling and simulation tools, with built-in human-in-the-loop checkpoints. The certifiable framework is rooted in LHP's Functional Safety and ASPICE engineering practice.
Like hiring an engineer who is already trained the LHP way, then teaching that engineer your process. The result is a very good draft an engineer can use on a real project, with less time spent prompting and more consistent output from engineer to engineer.
See the artifact your team needs most
Choose the engineering artifacts you want to see DAI-SE produce, and we will build your demo around them.
Request this demo
Inside DAI-SE
See the artifact your team needs most
Choose the engineering artifacts you want to see DAI-SE produce, and we will build your demo around them.
Request this demoBuilt to be governed, not just prompted
Skills carry a status
Engineering skills are catalogued and marked validated or draft, so a program draws on methods that have been reviewed rather than whatever the model improvises.
Workflows encode your process
Stages, gates, work products, playbooks and the skills available at each stage are configured per workflow, including V-model layouts.
Access is scoped
Customers, projects, groups, users and skill packages are managed separately, so each team sees only what it should.
Skills are packaged by role
A package maps a set of skills to a group, so an engineer gets exactly the set their role needs.
Traceability top to bottom
With an audit and evidence record behind it.
The engineer stays in the loop by design
DAI-SE plans, drafts, checks itself against a defined pass bar, and recommends. A person reviews and approves.
Into your ALM, and into your development toolchain
Your ALM
DAI-SE reads the ALM's item types and proposes the mapping, with its reasoning for each rule. Then it pushes every requirement as its own item, trace links intact. The walkthrough shows 226 requirements landing in Jama as individual items. The same mapping approach works for any ALM with item types and trace links.
Your documentation
Connect a wiki or documentation space and the platform works from your own material rather than generic sources.
Your development toolchain
DAI-SE is also an MCP server. Point an agent harness at it, such as GitHub Copilot, Claude Code or Codex, and the agent gets the validated skills library along with the program's requirements, interface specification and test cases. Link Jira so stories flow back. Assign a story to a coding agent and it develops against those artifacts, and the pull request cites the requirements it implements, the interface it honors and the tests that verify it.
From the customer's statement of work to a pull request, with the thread intact the whole way.
Frequently asked questions
What is DAI-SE?
DAI-SE stands for Digital AI Specialized Engineer. It is a governed AI engineering platform from LHP Engineering Solutions that enables organizations to systematically generate high-quality engineering artifacts for controls development with AI, with consistency across team members. Those artifacts include ISO 26262 item definitions, functional decomposition, system requirements specifications, system and software architecture, SysML v2 and OPM models, and verification test specifications, with LHP's validated engineering skills built in. An engineer reviews and approves everything it produces.
Who is DAI-SE for?
DAI-SE is for engineering executives who want better AI adoption at scale for controls development, but are struggling to keep quality and consistency from general-purpose LLMs across their users. It gives a team one governed way to use AI, so output is more consistent from engineer to engineer and less time goes into prompting.
Is DAI-SE only for systems engineering?
No. DAI-SE is for controls development more broadly, and systems engineering is one part of it. It supports both systems engineering and software development workflows, and each team configures the workflow to match how it works.
How is DAI-SE different from a general-purpose AI assistant?
Three things. First, LHP's engineering knowledge is built in as a validated skills library, so DAI-SE starts out trained the LHP way instead of as a generalist. Second, a customer data layer lets your team add your own process documents, engineering data and subject matter expert knowledge in a structured way, so DAI-SE can produce outputs the way your organization already produces them. Third, a governed engineering framework connects DAI-SE to common engineering toolchains with human-in-the-loop checkpoints. The result is work that is close to usable out of the box, with less time spent prompting and more consistent output from engineer to engineer.
What can DAI-SE produce today?
In the demo session it produced sixteen artifacts filed by lifecycle stage: the item definition, functional decomposition, a system requirements specification with every requirement traced to its source element, system and software architecture across four layers, operating modes as a state machine, SysML v2 and OPM models, software requirements, and a verification test specification with each test linked to the requirement it verifies. Sixteen is what that walkthrough covered, not a limit, because skills can be added.
Does DAI-SE replace engineers?
No. DAI-SE plans, drafts, checks itself against a defined pass bar, and recommends. An engineer reviews and approves. At a gate review it will recommend a hold and cite the clause behind it, which is only useful because a person makes the final call.
Does DAI-SE perform functional safety analysis such as HARA?
No. DAI-SE produces engineering work products for controls development. Its outputs follow LHP's ISO 26262-aligned internal templates, which means the work sits inside a safety-relevant process, but DAI-SE does not perform hazard analysis or derive safety goals. LHP provides functional safety services separately.
Does DAI-SE connect to our requirements management tool?
Yes. DAI-SE reads your ALM's item types, proposes a mapping with its reasoning for each rule, and pushes every requirement as its own item with trace links intact. Demonstrated with Jama, and the same approach works for any ALM with item types and trace links.
Does DAI-SE work with coding agents and our repository?
Yes. DAI-SE runs as an MCP server, so an agent harness such as GitHub Copilot, Claude Code, or Codex can pick up the validated skills library along with the program's requirements, interface specification, and test cases, and develop against them. Pull requests cite the requirements they implement and the tests that verify them.
What happens when the customer has not decided something?
DAI-SE marks the interface or parameter TBD and writes the decision that has to be made. It does not invent a value to fill the gap.
Can we use our own process and data with DAI-SE?
Yes. Customers add their own process documentation and engineering data on top of LHP's skills library, and skills can be created from that material so the outputs follow your way of working. Work is organized into customers, projects and groups, so your data stays separate from other customers.
How is our data kept separate from other customers?
Work is organized into customers, projects and groups, and access to skills and work products is managed through packages mapped to those groups.
How do I get started?
Schedule a demo using the form on this page. LHP will walk you through DAI-SE and talk through how it applies to your engineering work.
Who builds and supports DAI-SE?
LHP Engineering Solutions, which has worked in safety-critical and mission-critical embedded systems for 25 years. DAI-SE is built by LHP solution architects and backed by LHP's engineering teams.
© 2026 LHP, Inc.