Veyra
Veyra is a Swedish manufacturing quality intelligence platform that unifies production data, statistical process control and capability analysis in one workspace, adding an AI assistant and an investigative agent for real-time monitoring and root-cause work on the factory floor.
What is Veyra?
Veyra is a cloud platform for manufacturing quality, published by the Stockholm company Dominion SPC AB. Its stated purpose is to unify production data, quality analytics and process control in a single workspace, and to make statistical process control accessible to factories of every size rather than only to those able to run specialist desktop software.
The starting point is data unification. Veyra ingests files such as Excel, PDF and DFQ exports, connects to systems including SQL Server, PostgreSQL and ERP platforms, and pulls readings from coordinate measuring and metrology equipment made by Mitutoyo, Zeiss and Hexagon. APIs and IoT devices are also listed as sources. Everything lands in one data model, which is what allows analysis to run across machines and sites instead of inside each silo.
On top of that sits a genuinely deep statistical layer, unusual for a product this young. It covers real-time SPC control charts with automatically derived limits, capability and performance indices (Cp, Cpk, Pp, Ppk) with explicit handling of non-normal data, Kolmogorov-Smirnov normality testing, Box-Cox and Johnson transforms, ANOVA, regression and correlation, plus histograms, goodness-of-fit tests, box plots and scatter plots.
The AI layer works at two levels. An AI Assistant follows the user through the product, explaining data, building dashboards and configuring the workspace with built-in manufacturing domain knowledge. An Agentic Playground runs multi-step deep-dive investigations alongside the engineer, described by Veyra as fully dynamic and fully traceable. Findings, process conditions, materials, machines, defects, root causes and corrective actions are connected into a single compounding graph so that knowledge accumulates across sessions.
Collaboration and reporting complete the picture: comments and mentions on charts and individual measurements, role-based permissions, scheduled or on-demand PDF and HTML reports, alerts routed to email, Microsoft Teams or Slack, and an audit trail of every change.
Veyra names three industrial customers publicly, all Swedish and all automotive-facing: AC Floby, Beslag & Metall and Alfdex. The company joined FKG, the Scandinavian automotive suppliers' association, in March 2025, and publishes a public glossary and blog covering SPC, capability, MSA, FMEA and IATF 16949.
What it does
- Connect any production data source into one unified model: databases, measurement machines, APIs, files and IoT devices
- Monitor processes in real time with SPC control charts and automatically calculated control limits
- Track capability and performance indices (Cp, Cpk, Pp, Ppk), including non-normal distributions
- Investigate a quality problem step by step with an AI agent in the Agentic Playground
- Receive alerts by email, Microsoft Teams or Slack when a control limit is breached or capability drops
- Run the wider statistical toolbox: normality tests, Box-Cox and Johnson transforms, ANOVA, regression and correlation
- Produce and schedule PDF and HTML reports, and collaborate on findings with comments, mentions and a full audit trail
When to use Veyra / When not to
A quick filter to help you decide if Veyra is the right fit.
When to use Veyra
- Quality engineers and quality managers in discrete manufacturing who need SPC charts, capability indices and root-cause analysis on live production data rather than on spreadsheet exports.
- Tier 1 automotive suppliers serving demanding OEMs, the profile of every customer Veyra names publicly: AC Floby, Beslag & Metall and Alfdex.
- Factories that have invested heavily in metrology and now find their measurement data siloed across machines, systems and file formats.
- Multi-site manufacturing groups looking to consolidate quality and process data from several plants into one shared workspace.
- Manufacturing and process engineers who currently spend hours stitching datasets together before they can produce a single report.
When not to use Veyra
- Buyers who need a public price before they will talk to a vendor: Veyra publishes no pricing page, no plans and no amounts anywhere on its site.
- Teams looking for self-service onboarding or a free trial, since every call to action on the site leads to a contact form.
- Organisations whose procurement requires published security certifications, a data processing agreement or a subprocessor list, none of which Veyra publishes.
- Users who need a mobile application: no iOS or Android app exists, and store searches only return unrelated third-party packages.
- Companies that need an interface in a language other than English or Swedish, the only two locales the site actually serves.
How to use Veyra
A typical end-to-end flow, from setup to results.
- Read the public glossary and blog to check that the statistical scope matches your quality process
- Submit the contact form on the Veyra site, the only entry point, since there is no self-service sign-up
- Use that first exchange to request a demonstration and ask for pricing, as the contact page itself suggests
- Scope the data sources to connect: measurement machines, databases, ERP, existing files and any IoT feeds
- Have the vendor provision your workspace and, if you need programmatic ingestion, your API credentials
- For file ingestion, call POST /v1/signed-urls with your X-Customer-ID and X-API-Key headers to obtain a signed upload URL
- Upload each file with a PUT request to that URL within the fifteen minutes it stays valid
- Build dashboards combining SPC charts and capability KPIs, and pin the views your team needs daily
- Configure alert thresholds and route notifications to email, Microsoft Teams or Slack
- Move day-to-day work into the platform: comment on findings, assign corrective actions and schedule reports to stakeholders
Pros & Cons
Pros
- Statistical depth that goes well beyond basic charting, including non-normal capability, Kolmogorov-Smirnov testing and Box-Cox and Johnson transforms
- Connectors that reach the actual sources of factory measurement data, naming Mitutoyo, Zeiss and Hexagon alongside SQL Server, PostgreSQL and ERP systems
- A two-level AI layer: in-context assistance for everyday use and an investigative agent presented as fully traceable
- Named industrial customers with attributed testimonials from identified quality leaders, not anonymous logos
- Membership of FKG, the Scandinavian automotive suppliers' association, which is a verifiable industry signal
- A documented public API described in an OpenAPI 3.1 specification for programmatic file ingestion
- Alerts routed to the channels teams already use, and a bilingual English and Swedish site with a genuinely useful public glossary
Cons
- No public pricing at all: no pricing page, no plans and no amounts anywhere on the site
- No free trial and no free plan is announced, and there is no self-service demo either
- No terms and conditions, no data processing agreement and no subprocessor list are published
- No security certification is claimed; the ISO 9001 and IATF 16949 mentions on the site are glossary entries, not credentials held by Veyra
- The privacy policy covers only the marketing website, leaving the treatment of customer production data undocumented
- No hosting country or region is disclosed, and nothing is published about model training or an opt-out
- A very young and very small publisher: the legal entity was registered in November 2024 and the 2025 accounts report five employees
Pricing & Plans
Veyra does not publish any price. There is no pricing page on the site, no plan names, no amounts and no currency, and no free plan or free trial is announced anywhere. The contact page invites visitors to ask about pricing, which makes commercial contact the only route to a quotation. Prospective buyers should therefore budget for a sales conversation and expect terms to be negotiated per deployment.
Data, GDPR & hosting
A consolidated view of how Veyra handles your data.
GDPR overview
Veyra is operated by a Swedish company, so the GDPR applies as a matter of law, but the word GDPR is never used anywhere on the site. The privacy policy, effective 12 February 2025, lists three data subject rights: access to the personal information held, correction or update, and deletion. All of them are exercised through the contact form; no privacy or DPO email address is published, and no data protection officer is named. One retention period is stated: job application data is kept for up to two years. The document's scope is expressly the website and recruitment. It says nothing about the production and quality data the platform itself processes, and there is no data processing agreement, no subprocessor list, no hosting location and no transfer clause. Any GDPR assessment of the product must be obtained from the vendor.
Who owns the data?
Veyra publishes no terms and conditions, so no contractual clause on data ownership, intellectual property or licence grants is available. The only legal document on the site is a privacy policy whose scope is expressly the website: visitors and job applicants. It states that information submitted through forms is stored securely and that Veyra does not share or sell it to third parties without explicit consent, except where required by law or to fulfil the purpose of collection. Nothing addresses ownership of the production and measurement data customers push into the platform. The published API does reference a customer-specific ingest bucket, which implies per-customer isolation, but that is an implementation detail, not an ownership statement.
Reuse rights
Nothing on the site tells a customer what they may do with the data they get back, because Veyra publishes no terms of service. The privacy policy covers only website usage: Google Analytics collects pages visited, device and browser type, time on page and IP-based location, described as anonymised and used for statistics only; a LinkedIn Insight Tag tracks conversions, retargets visitors and aggregates demographic data such as job titles and industries. Form submissions are used to answer enquiries and process requests. Job application data is used strictly for recruitment. For the production data the platform actually analyses, there is no published statement on reuse, redistribution, export rights or model training. Treat every such question as open until the vendor answers it in writing.
Data retention & training
Hosting summary
Veyra discloses nothing about where customer data is hosted. No country, no region and no cloud provider is named on any page of the site, and the privacy policy mentions no hosting arrangement, no processor and no international transfer. There is no trust or security page. Two technical clues exist but are not vendor statements and have deliberately not been treated as facts about the service: the site itself is served from Google infrastructure, and the published API specification shows a signed upload URL pointing at Google Cloud Storage in an example response. Neither identifies a region. The API does describe a customer-specific ingest bucket per customer, which suggests tenant isolation at the storage layer, again without any location. For a Swedish vendor selling to European manufacturers, the absence of a stated jurisdiction is a gap worth closing in writing before any deployment involving production or personnel data.
Things to keep in mind
Risks and trade-offs to weigh before adopting Veyra.
- The site declares a 2023 founding date in its llms.txt and structured data, while the Swedish register shows the legal entity Dominion SPC AB was registered on 5 November 2024; 2023 is when the founders met at Northvolt, not when the company existed.
- The three headline metrics on the home page are animated counters: the served HTML contains only zeros, so no figure behind 'faster data collection', 'days to uncover insights' or 'seconds to detection' can be verified.
- Because no terms and no data processing agreement are published, every contractual question about ownership, liability, service levels and processing of production data is open at the point of first contact.
- The privacy policy is scoped to the website and recruitment only, so it cannot be relied upon to describe how customer production data is handled.
- No hosting country or region is disclosed. Infrastructure clues exist, but the vendor does not commit to any jurisdiction, which matters for regulated or export-controlled manufacturing.
- The API documentation is linked from no page on the site and absent from the sitemap, so it can change or disappear without notice; treat any integration built on it as needing its own contractual cover.
- Concentrating quality judgement in an AI agent carries the usual risk of deskilling: the platform advertises traceability, but teams should keep validating agent conclusions against the raw measurements rather than accepting them by default.
Setup & Integrations
Technical difficulty
Setup starts commercially, not technically: there is no self-service sign-up, so the vendor provisions the workspace. The real effort is connecting existing sources, which is a project rather than a click: databases, ERP, measurement machines, files and IoT feeds have to be mapped into the unified data model. The documented programmatic path is simple in itself, requiring two authentication headers and a signed upload URL valid for fifteen minutes, but credentials are issued manually. Veyra advertises its AI Assistant as helping configure the workspace. No installation guide or public getting-started documentation exists.
Deployment
Integrations
Supported languages
Behind Veyra
Fundraising
Social
Resources
All the official URLs gathered for verification and reference.
Frequently asked questions
What is Veyra?
Which statistical methods does Veyra actually cover?
What data sources can Veyra connect to?
Where does the AI actually intervene?
How much does Veyra cost?
Is there a free trial or a free plan?
Does Veyra have an API?
Is there a mobile app?
Who is behind Veyra?
Which languages does Veyra work in?
Should you pick Veyra?
Veyra is a narrow, credible product rather than a general-purpose analytics tool. It targets one job precisely: turning the measurement data a discrete manufacturing plant already generates into live process control, capability tracking and root-cause work, in a single workspace. The statistical scope is unusually serious for a company this young, and the AI layer is more than a chat window: an in-context assistant plus an agent that runs multi-step investigations and feeds a knowledge graph the factory keeps.
The commercial signals are real and checkable. Three named industrial customers were announced between November 2025 and April 2026, all automotive-facing Swedish manufacturers, with testimonials attributed to identified quality leaders. Veyra joined FKG, the Scandinavian automotive suppliers' association, and closed a SEK 6 million pre-seed round led by the founders of Sambla.
Against that, the transparency is thin. There is no published price, no terms and conditions, no data processing agreement, no subprocessor list, no security certification and no disclosed hosting location. The only legal document, a privacy policy, covers the marketing website and says nothing about the production data the platform actually processes. Nothing is published about model training or an opt-out. The publisher is also young and small: the legal entity was registered on 5 November 2024 and the 2025 accounts report five employees.
For a quality function that recognises its own problem in Veyra's description, this is worth a conversation. Just go into it knowing that evaluation cannot start from the website: pricing, contractual terms, hosting and data governance all have to be obtained from the vendor before any serious comparison is possible.
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