Build the Future of Decision Intelligence.
We are building the mechanism that turns operational data into decisions people can defend. It is a hard problem, and it is the whole job.
Where the work happens.
AI
Agent orchestration, reasoning quality and grounded answers.
Machine Learning
Forecasting and decision models fitted to real operations.
Data
Ingestion, canonical modelling, retrieval and knowledge graphs.
Software Engineering
Platform, integration and the interfaces people decide in.
Product
Turning operational problems into decisions the platform can carry.
Sales
Working with organisations across industries on real decisions.
Customer Success
Pilots that get measured, and deployments that keep delivering.
Currently hiring.
No open roles right now
We are not advertising a position at the moment, but we always read a good speculative application. Tell us what you would want to work on and why.
Small team, real ownership.
Veraius is early. That means the person who builds a thing also decides how it should work, talks to the customer using it, and lives with the consequences.
Close to the problem
Engineers join customer conversations. You cannot model a plant's decisions well from a ticket description.
Measured, not asserted
We check claims before we ship them — about accuracy, about performance, and about what the product actually does.
Written down
Decisions and their reasoning are documented. It is the same discipline the product sells, applied to ourselves.
What to expect when you apply.
Four steps, and we tell you where you stand after each one.
Intro call
Thirty minutes on what you want to build and what we are building.
Working session
A real problem from our domain, worked through together. No algorithm trivia.
Meet the team
The people you would work with day to day, and your questions for them.
Offer
Scope, level and compensation explained in full, with time to consider it.
What your teams gain from Veraius agents.
Budget against reality
Planned and actual spend are compared by cost centre, and variances above your threshold are escalated with their cause.
See the Finance agents SalesKnow which lead is worth the call
Inbound leads are scored hot, warm or cold from their behaviour and fit, and routed to the right owner.
See the Sales agents ManufacturingCapacity against orders
Open orders are compared with available capacity so delivery risk shows before a due date is missed.
See the Manufacturing agentsIn every department
- Agents prepare the work on your own data; your people approve what happens next
- Plain-language questions answered from live ERP data, with tables and interactive charts
- Grounding check: numbers that cannot be traced to a source are not shown
- Explainability, confidence and risk scores with decision rationale
- Slack, Teams, WhatsApp and Signal channels with an approval inbox
- Department-based access policy with personal data masking
Frequently asked questions
Straight answers about integrations, deployment, security and cost — including where the honest answer is "it depends".
Ask your own questionWhat kind of people are you looking for?
People who want to understand the operation, not just the model. The interesting problems here are at the boundary: why a planner overrides a correct recommendation, what a lead time distribution means when the supplier changed hands last year. A strong engineer who is incurious about the domain will not enjoy this work.
What does day-to-day work at Veraius involve?
Reading real data from real factories and stores, building the models that decide on it, and being in the room when someone disagrees with the output. Most roles here involve customer contact regardless of title, because a decision system cannot be built at arm's length from the decision.
Do you hire remotely?
For some roles. The constraint is not preference but the nature of early deployments, which involve being on site while an operation is understood. Roles further from that work are more flexible.
What if no open role fits my profile?
Write anyway, and be specific about what you would want to work on. A small team hires against a person more often than against a job description.