Pilot-ready automotive engineering platform

Trizon V-Foundry

Turn engineering intent into traceable evidence.

A governed AI orchestration platform for automotive software teams—connecting requirements, architecture, code, verification, documentation and delivery across the complete V-cycle.

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Automotive-grounded agents Human approval gates Customer-hosted or managed cloud Existing tools remain authoritative

Why V-Foundry

The bottleneck is not code alone. It is engineering continuity.

Automotive programmes lose time when requirements, standards, source code, verification evidence and release documentation live in disconnected tools. General-purpose copilots can draft content; they do not, by themselves, preserve project context or lifecycle accountability.

  1. 01

    Context is fragmented

    Specifications, OEM rules, safety analyses, vendor packages and historical decisions are difficult to retrieve together at the point of work.

  2. 02

    Handoffs break traceability

    Intent is repeatedly translated between requirements, design, implementation, testing and documentation—creating ambiguity and rework.

  3. 03

    AI output needs controls

    Safety-relevant engineering requires declared inputs, bounded resources, review gates, reproducible runs and a clear audit trail.

  4. 04

    Value must be proven locally

    Productivity depends on task, toolchain and baseline maturity. V-Foundry measures improvement against your own workflow, rather than promising a universal percentage.

One engineering thread

AI assistance across the V-cycle—without removing engineering ownership.

V-Foundry assembles specialist agents into reviewable workflows. Each run is grounded in approved project resources and produces artefacts that engineers can inspect, correct, approve and export.

Intent → artefact → evidence

A continuous thread links the input used, the action performed, the output created and the verification applied.

Define

Requirements

Clarify, structure, decompose and check consistency.

Design

Architecture

Draft interfaces, allocations, rationale and reviews.

Build

Implementation

Plan changes, generate code and prepare diffs.

Verify

Unit & Integration

Create tests, analyse logs and collect results.

Validate

Qualification

Assemble coverage, consistency and evidence packs.

Release

Documentation

Render controlled work products and change records.

Grounded project knowledge
Versioned agents & skills
Human review gates
Run history & trace links

Platform capabilities

A governed workbench built around automotive engineering work products.

Configure reusable components for your domains, standards, toolchain and approval process—then compose them into executable workflows.

Workflow Workbench

Build visual, reusable agent workflows. Run, dry-run and inspect each step with live logs and clearly defined inputs and outputs.

Orchestrate

Agent & Skill Library

Manage domain agents and auditable skills with prompts, schemas, parameters, tool permissions, lifecycle status and run history.

Reuse

Engineering Knowledge

Ground agents in approved standards, project documents, OEM practices and decisions using per-project retrieval with source references.

Ground

Code Context

Index authorised repositories and reference packages for joint search, code explanation, change planning, test generation and review.

Build

Work-Product Templates

Use versioned templates for systems, software, safety, security and verification artefacts; pre-fill outputs while keeping review ownership explicit.

Document

Engineering Dashboard

Track project artefacts, workflow runs, pending reviews, agent activity and delivery status while retaining ALM and Git as sources of truth.

Govern

Designed for controlled engineering

Every agent operates inside declared boundaries.

V-Foundry is an engineering accelerator—not an autonomous safety authority. Customers define the policies, resources and approvals that apply to each workflow.

Important: Alignment features can support your Automotive SPICE®, ISO 26262, ISO/SAE 21434, AUTOSAR and coding-standard workflows. They do not constitute certification, compliance approval or a substitute for competent engineering review.
01

Resource boundaries

Agents access only the knowledge, repositories and tools explicitly assigned to them.

02

Versioned components

Prompts, skills, models, parameters and templates follow controlled lifecycle states.

03

Human approval gates

Engineers review diffs, findings and work products before controlled-system updates.

04

Auditable execution

Run history records inputs, outputs, checks, status, model route and reviewer decisions.

05

Cost and model policy

Route work by task, confidentiality and budget with model allowlists and usage controls.

Two deployment models

Choose where your data, models and inference run.

The application layer, integrations and engineering controls remain consistent. Infrastructure, model access and commercial structure adapt to your security posture.

Maximum sovereignty

Customer-hosted

Deploy within the customer’s controlled AI environment—on premises, private cloud or an approved restricted network—subject to infrastructure readiness.

  • Customer-controlled data boundary and identity policies
  • Private model endpoints or approved self-hosted models
  • Integration with internal Git, ALM, CI/CD and document systems
  • Configurable logging, retention and network-egress policy
  • Suitable for sensitive source code and engineering artefacts
Commercial model: platform licence, deployment/integration and support. Customer provides or funds the required compute infrastructure.
Fastest route to pilot

Managed public cloud

Run on supported public-cloud infrastructure with approved commercial model APIs and policy-controlled access to customer resources.

  • Faster environment provisioning for scoped pilots
  • Model choice based on task, quality and cost requirements
  • Token usage metering and per-agent spending controls
  • Encrypted transport, access controls and configurable retention
  • Can transition to customer-hosted deployment as needs mature
Commercial model: platform and integration charges plus metered model-token and infrastructure consumption.

Fits your engineering ecosystem

Add an AI layer without replacing systems of record.

V-Foundry is designed to connect through APIs, repositories, webhooks and controlled import/export paths. Actual connectors are agreed during solution design.

Requirements & ALMGit & code reviewCI/CD & quality gatesTest automation & HIL/SILStatic analysis & coverageDocument repositoriesIssue & change trackingEnterprise identity & audit

Start with a bounded pilot

Prove value on one real workflow before scaling.

A pilot should test quality, effort, traceability and integration against an agreed baseline—not simply demonstrate generated text.

Select the workflow

Choose a repeatable, evidence-rich use case such as requirement refinement, test generation, log triage, safety work-product drafting or code review support.

Secure the context

Define authorised data, repositories, standards, model route, identity controls and the required deployment topology.

Configure & integrate

Adapt agents, skills, templates and checkpoints to the customer’s actual process and toolchain.

Measure & decide

Compare baseline and assisted execution, review failure modes and establish the case for controlled expansion.

Engineering effortReview turnaroundOutput acceptance rateRequirement-to-test coverageDefect escapeReworkAudit completenessToken / compute cost

Bring one automotive workflow. We’ll show how to make it agent-ready.

Book a working session to map your use case, deployment constraints, toolchain integration and pilot success measures.

Book a Demo Or write to info@trizon.ai

Trizon V-Foundry is currently offered as a configurable pilot solution. Feature availability depends on the agreed scope, deployment topology and integrations.