// solutions.test_and_compliance
Runa vendor's AIagainst a twin of production. Nothing it touches is real.
Veris stands up a working replica of your production environment: the same systems, the same data shapes, the same people around it, sealed off from the real one. Evaluate what you're buying and what you're building in the same place, under your own operating conditions.
- a twin of your production environment: simulated tools, services, and users
- air-gapped from production, with no network path back
- one environment for the AI you buy and the AI you build
// the_problem
The hard part of AI is proving what it will do, and most institutions have nowhere safe to find out. So AI either waits three quarters for an environment, or goes straight to production and lets real customers be the test.
Before
The AI you buy arrives with a demo on the vendor's data and claims you can't check. The AI you build passes the tests your own team wrote for it. Neither tells you what happens under real conditions, so the choice comes down to a review that outlasts its budget or shipping on faith. Either way, your customers meet the failures first.
With Veris
A twin of production, already standing and already sealed. Everything you buy and everything you build runs against your real operating conditions in days. Compliance, cost, and risk are on the table before you sign the contract or open the traffic, and the evidence is written down.
// how_it_works
The Veris loop
The same four moves on every Veris page, voiced for this job.
// the_engine_underneath
One engine. Simulated worlds.
Every Veris solution runs on the same simulation engine. Compose an environment by listing the systems in your stack (databases, APIs, MCPs, and the humans in the loop) and describe a scenario in plain language. The engine simulates that world: actors stay on goal and behave like people, services stay consistent and high-fidelity, and every run is isolated and repeatable.
Runs in your VPC · SOC 2 Type II · Thousands of concurrent agents · Synthetic data or your own
Explore the platform →…and dozens more, from banking cores to ERPs — or bring an API spec and Veris builds the simulator
// what_you_get
What you get
01Air-gapped by construction
The twin has no route to production — not a firewall rule, not a policy someone can grant an exception to. Nothing under evaluation can reach a real customer, move real money, or read a real record, because the path does not exist. That is a sentence your CISO can sign.
02One yardstick, every candidate
Three vendors and your own team's build, in the same twin, against the same conditions, in the same week. Any system that makes a decision faces the identical test: a model, a copilot, a document reader, an old rules engine with a new LLM bolted on. Vendor claims become measurable.
| Vendor A | Vendor B | Vendor C | In-house | |
|---|---|---|---|---|
| Policy adherence | ✓ | ✓ | ✕ | ✓ |
| Disclosure rules | ✕ | ✓ | ✕ | ! |
| Handles bad input | ! | ✓ | ✓ | ✓ |
| Escalates correctly | ✓ | ✓ | ! | ✕ |
| Data residency | ✓ | ✓ | — | ✓ |
| Cost per case | ! | ✓ | ✓ | ✕ |
03The cost, before you commit
A demo never tells you what a system costs at your volume. Run each candidate at real load in the twin and the trade-off becomes a number: what quality costs, what the cheap option gives up, and where your workload actually lands on the curve.
04A packet your board can read
Not a dashboard someone has to interpret. A decision packet in plain language: what each system did, where it failed, what it costs, and the full record behind every line, reproducible and defensible to an auditor or a regulator a year from now.
// before_you_ask
Questions your security review will ask
$Can anything in the twin reach our production systems?
No. The twin is built with no network route to production, and no policy can grant an exception to a path that does not exist. The systems inside the twin are simulations, so a vendor's AI running there never touches a real customer, a real ledger, or a real record.
$Do we have to hand over real customer data?
No. The twin runs on synthetic data that carries the shape, logic, and messiness of yours without containing anyone's actual information. If you would rather use your own data, it runs inside your VPC under your existing controls, and it never leaves.
$Does the vendor see our environment or our data?
The vendor's system runs inside the twin and is evaluated there. It sees simulated systems and synthetic records. It does not learn your production topology, and it does not take anything home.
$Is this only for AI agents?
No. Anything that makes a decision can be evaluated in the twin: a model, a copilot, a document reader, an agent, or a rules engine that recently had an LLM attached to it. If it acts on your business, it can be tested against your conditions.
$How is this different from our staging environment?
Staging drifts from production, is shared, and is usually connected to something real. The twin is rebuilt to match production, is isolated by construction, and is disposable, so a candidate can be pushed until it breaks without anyone filing a change request.
$What do we actually walk away with?
A decision packet: a written recommendation, the failures found and where, the running cost at your volume, and a reproducible record of every run behind it, the artifact your risk committee and your auditor both need.
// book_a_demo
See it on your stack.
Book a walkthrough on an environment like yours — or take a sample report with you first.
Book Demo →