About us
Trust Quality Assurance was founded by people who ran plant quality functions and spent their evenings reconciling data from three systems to answer one question. The product is the tool we wanted then, built to the standard an auditor would accept.
Mission
Make quality drift visible while it can still be corrected, in every plant, on every shift — and make the evidence of control available the moment someone asks for it.
Vision
A manufacturing industry where quality decisions are made from live, shared data rather than from end-of-shift reports and institutional memory.
How we operate
These are the rules we apply when a commercial incentive and an engineering judgement disagree.
We record a baseline before changing anything and report against it, including when the result is smaller than the customer hoped.
Product claims are written by the engineers who built the feature. If a capability has limits, the documentation states them.
Process parameters, recipes and images stay inside the customer tenant. No cross-customer model training, ever.
If the data or the process discipline is not there yet, we say so and propose what to fix first rather than selling a deployment that will fail.
Leadership
Every member of the leadership team has either run a quality function or built industrial data infrastructure at scale.
Chief Executive Officer
Twelve years in automotive quality management, including plant quality director for a tier 1 supplier across four European sites. PhD in production engineering.
Focus: Customer outcomes, enterprise agreements
Chief Technology Officer
Built industrial data platforms for battery and semiconductor manufacturers. Previously principal engineer on a high-throughput historian and analytics stack.
Focus: Architecture, edge and platform reliability
VP Applied AI
Computer vision and anomaly detection in industrial inspection. Led model governance for a regulated medical device programme.
Focus: Model quality, explainability, governance
VP Engineering
Distributed systems and platform engineering. Scaled a multi-tenant industrial SaaS platform from single-site pilots to global deployment.
Focus: Delivery, developer experience, quality of the codebase
VP Customer Success & Solutions
Quality engineer turned solution architect; ran multi-plant QMS rollouts in electronics and medical devices before joining.
Focus: Deployment, adoption, measured value
VP Security & Compliance
Information security leadership in regulated manufacturing, including SOC 2 and ISO 27001 programme ownership and validated-system change control.
Focus: Security programme, validation, customer review
Engineering culture
Manufacturing customers run our software for a decade. That constraint shapes how we write, review and release it.
Solution architects and product engineers spend time on customer shop floors every quarter. Feature decisions are argued with plant evidence, not personas.
Small changes, mandatory review, feature flags and staged rollout. Validated tenants are pinned and updated only inside agreed windows.
A feature is not done until the documentation and the API reference describe it, including its limits and failure behaviour.
Technical questions reach someone who can read the code. There is no scripted first line between a customer engineer and ours.
Technology stack
The same build artefacts run in managed cloud, in a customer's own subscription and inside an air-gapped plant network.
Chosen for predictable memory use and long uptime on plant hardware.
Sub-second query on hot partitions with retention measured in years, not weeks.
Every released model is versioned, monitored for drift and reversible.
The same artefacts deploy to managed cloud, private cloud and air-gapped sites.
Quality commitment
It would be difficult to argue for measured process control while running an unmeasured engineering organisation. These are our own operating numbers.
Every release ships with documentation, API reference updates and regression evidence. Validated tenants are pinned and updated only in agreed windows.
Customer-impacting incidents get a written post-incident review with timeline, cause and corrective action — the same standard we ask of suppliers.
Quality leaders from six sectors review the roadmap quarterly. Features that no plant will operate do not get built.
Global presence
Deployment support is delivered in the customer's time zone. Data residency follows the region, not the office.
Germany
Headquarters · engineering, solutions
Coverage: DACH, Northern and Southern Europe
United States
Americas customer engineering
Coverage: North America, Mexico
Singapore
APAC solutions and support
Coverage: Southeast Asia, Japan, Korea
Poland
Platform engineering
Coverage: Global engineering delivery
Careers
We hire people who are comfortable being wrong in front of a plant manager and correcting it with data. Every role involves customer contact.
Own technical delivery for multi-plant rollouts: data assessment, characteristic modelling and integration design.
Build and govern defect classification models running at line rate on customer inspection hardware.
Extend the edge gateway: protocol coverage, buffering guarantees and on-device inference performance.
Practising quality engineer who helps customers design control plans and sampling strategies that survive production.
Own validation packages and customer audit support for ISO 13485 and 21 CFR Part 11 programmes.
Contact
Enquiries go to the team that owns the answer. Security and validation requests are normally answered within two business days.
Start the evaluation
Bring one line, one defect family or one audit workflow. We will map the available data sources, quantify the cost of the current detection delay, and show the fastest route to measurable control.
45-minute technical walkthrough
With a solution architect who knows manufacturing data, not a scripted demo.
NDA before any data review
We can assess feasibility from sample exports without production access.
Written pilot scope
Baseline metrics, success criteria and exit conditions agreed up front.