Nx·Studio scores design options for each process you put forward, and your IT team deploys the one you select. Nx IDE gives the engineers who serve your backlog more delivery capacity, under approval controls. The Cognitive Engine settles routine cases without an AI call, once it has scored perfectly on cases it has never seen.
Define the workflow and expected outcomes. Evaluate digital workers against process volumes, review effort and operating costs before deciding where to expand automation.
Each test run uses synthetic data, with accuracy, cost and safety measured before any customer, supplier or ledger is involved.
The generated software belongs to your organization and runs under your control. Nxgyle charges no fee per decision, so higher volume does not raise our fees.
Rules that repeat exactly, logic auditors can read and a record of every approval. We concentrate on finance, healthcare and comparable regulated fields.
Nx IDE has 31 built-in modes: ten core modes and 21 specialists. With the Orchestrator, every change is tested and reviewed by modes separate from the one that wrote it, and your engineers decide whether it ships.
Your engineers select from 20+ supported AI providers, including local models, and confirm each model's suitability, data settings and cost.
As shipped, AI actions in the editor wait for human approval. Teams can add allow / ask / deny rules, their own checks, optional cost limits and one-click rollback.
Cortex maps your systems' code locally on the engineer's computer, without network calls, and rates how risky each planned change is before anyone approves it.
Approval points, thresholds, escalation paths and assigned reviewers appear in advance, on the canvas or as swimlanes, so your risk colleagues can assess the controls before live use.
Every approval is recorded. Options add a tamper-evident log of each run and a trace showing where every data value came from. Auditors can ask us for the audit-trail specification.
Every export contains a signed inventory of everything inside the software, which your IT team can verify, plus a security analysis for your IT security team. A valid signature shows the package is intact; it does not certify security or compliance.
A process description in writing is enough to scope it, and testing can use synthetic data alone. Agree confidentiality and data-handling terms before any real records are shared.
A process you put forward becomes a worker your organization keeps. Each step shows its evidence beside the claim, so you decide on facts.
Pick a priority process, such as invoice matching or claims intake. A short written paragraph is enough, or your team can follow a guided form of ten steps. Supporting documents can be attached, and optional modules accept logs from process-mining tools, source code from your current agents, or standard process diagrams. Shared material is used for designing your workers and nothing else, under data-processing terms agreed in advance.
Scoping needs only your written description, and test runs can use synthetic data throughout, so no production records change hands.
Nx·Studio’s AI business analyst offers a shortlist of no more than five designs, from cautious to compliance-first, scores each and recommends one. Designs that fail its checks are retried or dropped. Each business rule it drafts needs your acceptance or edits before it applies. For connections to your systems there is a catalog of integration connectors and starter code. Its SAP, Oracle EBS, Workday, Salesforce and ServiceNow entries are starter code your IT team completes. Each connection still needs compatible interfaces, credentials and testing by IT.
Each design is derived from your own process description or a catalog template you configure, and its blueprint is readable before the first test run.
Testing uses synthetic data created around each worker's process. Your team can check one stage or the complete flow, including its approval pauses. Several workers may also be tested at once on accelerated time, with simplified stand-ins by default and the real workers on request. An optional red-team test checks how they hold up against known attack techniques.
Every test run gets a scorecard; accuracy, cost and safety are three of its measures. Compare competing versions on one scenario and see what each run cost.
Once results meet your criteria, export the complete software, ready for your IT team to deploy on your own cloud or servers. It runs on supported AI providers, local models included, once IT validates its configuration. It needs no Nxgyle software to run, carries no fee per decision and never calls home.
What the export containsA signed inventory of everything inside the software lets your IT team verify the delivery offline, and an ownership report lists what you received.
Nx·Studio, the flagship, turns one of your processes into a digital worker you can test first. Nx IDE gives your engineers more delivery capacity. The Cognitive Engine settles routine decisions once its rules are proven. The Foundation is what your reviewers check. Each product is scoped on its own, against your business goals.
Pick one process, such as supplier invoices. Nx·Studio drafts up to five alternative designs with estimated monthly cost and hours saved, then tests your pick on sample data.
More delivery capacity from the engineers behind your business backlog. AI modes in VS Code plan, code, test and review changes; the editor asks an engineer before each action by default.
Settles routine decisions, such as warranty claims, with no AI call once its rules are proven. Each rule learns from outcomes your team confirmed, then sits a blind exam first.
What risk, IT and audit colleagues can check before rollout: test results, the rules applied and a signed list of everything inside the software.
When AI models perform alike, the difference lies in how a worker is built and checked. The Foundation under each Nx·Studio worker gives your operations, IT and risk colleagues four mechanisms to test, read and verify, rather than take our word for it.
Each worker gets synthetic test data shaped around its own process, so evaluations use believable cases while customers, suppliers and the ledger stay untouched. Runs can cover one step or the whole flow, and they stop at each approval until the reviewer answers. You can also test workers side by side on accelerated time, using stand-in responses or, if you prefer, the real workers. Scorecards cover accuracy, cost and safety for each run. Production data is never a prerequisite.
List the rules your business must follow, such as approval limits or payment terms, and the AI analyst encodes each one as a fixed check wherever it can. Nothing it drafts takes effect until you accept or edit it, and the analyst reports the rules it was unable to encode. Given the same inputs, a fixed check always reaches the same result and never consults an AI model. A separate product, Nxgyle's Cognitive Engine, covers routine decisions no one has documented: it learns them from confirmed outcomes, outside Nx·Studio workers.
Each worker is described in plain language: every step, approver, escalation point and connected system, with nothing hidden in prompts. Every save is stored as a version, so any two can be diffed, merged or reverted. Business teams see the same design as a lane chart of the teams, people and systems involved, while the export screen gives an itemized list of the build. The blueprint is yours to keep, as is everything else the platform generates.
You see the full contents on the export screen before downloading. Inside is a signed inventory of everything in the software, including its AI components, which your IT team can verify offline with the bundled checker. It also contains a security analysis for your IT security team, plus draft documents for the European Union's AI Act. Once delivered, it needs nothing from Nxgyle to run, with no license check, no metering and no calls home.
AI handles judgment calls; your people make the decisions you reserve for them. At each approval step the worker waits for the assigned reviewer. When a workflow has approval steps, the export contains a reviewer inbox for your IT team to connect, and Slack can be added as a channel. Confidence thresholds are configurable too: a low score raises a warning by default, or can send the case to a person.
Many automated processes query an AI model for each decision, including ones made hundreds of times before. The Cognitive Engine runs alongside your agent systems and takes on that repetitive work. Outcomes confirmed by your records or reviewers are its only lessons, and each rule must pass an exam first. After that, it settles a matching case in milliseconds without calling AI, and you can read every rule in plain words.
Your agent systems connect to it through the decision interface its Studio provides. To date, every figure was recorded on simulated businesses with synthetic data.
A model's answer is never training evidence.
By default, 400+ cases it has never seen, every one correct.
No AI call, and the same answer from the same version.
Anything outside its training goes to a person for review; an AI route exists only if you enable it.
Every digital worker runs from a blueprint, a readable and versioned record. It shows who does what, which systems it uses, where approvals sit, how cases are routed and which rules apply. Changes are reviewed there, not hidden in prompts or a vendor's software.
Illustrative: two versions that differ in one approval rule, described in plain words. Your claims team reads the blueprint as a lane chart of who and what is involved. Engineers compare versions like code, and auditors get a plain summary of the build. The Studio checks each saved version and exports it for the cloud you select, so the logic and its history stay with your organization for every future review.
Set the expected cost per case against the hours and cycle time your team gets back. Stated business rules are encoded as fixed checks where they can be, and such checks never consult an AI model. Every design option comes with an AI estimate of its monthly running cost and the time it could free up. The Studio also points out where a worker could become more predictable and cheaper to run.
Any AI judgment left in the design runs on model accounts of your choosing, including local models. You can also cap the steps and duration of each run. If your agent systems face identical decisions all day, the qualified routine ones suit the Cognitive Engine, which settles them without model calls. The engine stands apart from Nx·Studio workers and connects through its own Studio.
Because your IT team runs the exported software, no runtime license is needed and no meter counts your decisions. Delivery and support are scoped on their own terms; your AI provider bills you directly for the model calls your workers make.
Agree design and delivery scope before implementation. No Nxgyle runtime license applies after export; infrastructure and AI usage remain operating costs. Ongoing support is optional and scoped to your requirements.
Each rule encoded as a fixed check is evaluated without a model call. That zero comes with the design; it is not a discount.
For each design option, AI estimates monthly operating cost and the hours your team gets back, while the generation plan carries a payback estimate. All three are planning inputs, and test runs log the real cost per run.
Your IT team runs the exported software. No runtime license is involved, and no Nxgyle meter climbs with volume.
Bring them to every shortlist review and compare the answers side by side. We publish the list knowing we can answer every item.
Can my risk and audit colleagues review how the worker decides before it handles live cases?
If we end the contract, which processes keep running?
Do we receive the complete software, or only access to it?
What happens to our bill if case volume doubles next quarter?
How are routine approvals protected if the AI model starts behaving differently?
Could a cleverly worded request talk the worker out of our policy?
Is the version we test the same software we would run?
Can we see it handle realistic cases before any customer or supplier is involved?
Must our customer data leave our control during the evaluation?
Is each approval enforced by the software itself, or by a setting someone can change?
Can our IT team prove we are not locked in, on our own hardware?
Does every figure in your proposal say how it was measured?
This page sets out our answers.
Shared definitions keep an evaluation precise, so here is what three key words mean on this site:
One business process, handled start to finish by software that applies your rules and approval steps.
A plain description of how the worker handles your process, kept version by version so reviewers can check every change.
The complete software, deployed and maintained by your IT team in your own environment; it needs no Nxgyle software to run.
See a sample export packageBusiness applications represented in the published industry catalog.
Defined workflow records across the published enterprise applications.
Catalog coverage across finance, healthcare, manufacturing, energy, legal, logistics, automotive and more.
Counts reflect published catalog records, not customer deployments or measured business results. Each digital worker runs a defined business workflow under configured rules and approvals. Nx·Studio exports its source code, which your organization then operates and maintains.
Nxgyle scopes, designs and delivers the whole workforce and can handle later upgrades. Everything delivered is yours.
Specialists who design and extend AI agent systems, plus the software that surrounds them, sequenced to fit your roadmap.
AI specialists and experienced engineers placed within your teams to add capacity where your priorities need it.
