One platform. Describe it, build it, own it.
Nx·Studio generates the digital workers that run your business. Nx IDE is there when you want to build or extend the software around them. The Foundation makes both predictable, explainable, and yours.
Three pillars. One owner: you.
Nx·Studio is the flagship; Nx IDE is the leverage; the Foundation makes both provable. Everything the three produce — workers, software, blueprints, audit trails — is delivered as source code you keep.
Nx·Studio
Describe a business process; an AI analyst designs a team of bespoke digital workers, rehearses them on the Simulated Enterprise, and delivers them as source code you keep.
- Generated from your context — no worker catalog, no templates
- Rehearsed on synthetic data before anything real
- 100% owned, self-hosted, no per-decision billing
Nx IDE
An AI coding agent in your editor that plans, builds, tests, reviews and ships the software your workers run in — on any model you choose, with an independent reviewer checking every change.
- Any model, your choice — never locked in
- An independent reviewer checks every change
- Git-backed checkpoints and one-click rollback
The Foundation
The layer both engines stand on — four named mechanisms that make every digital worker predictable, explainable, and provably yours.
- Routine decisions return the same answer every run
- Blueprints your auditors read before deployment
- The Ownership Audit ships in every export
Describe → Generate → Preview → Own
Your business description becomes a working digital workforce — and you own the code. Every step of the loop carries its own proof, in the same breath.
Start from a plain-language description.
Describe how your company works — a paragraph is enough. Prefer to ground it in your real estate? Documents, RPA definitions, and operational logs are design-time inputs you choose to share, used only to design your workers, with a data-processing agreement in place before anything moves.
A description-based evaluation shares nothing at all — every session runs on the Simulated Enterprise, on synthetic data only.
Bespoke workers, designed for your context.
An AI business analyst designs bespoke digital workers for your specific business — designed and previewed in minutes, not months. No worker catalog. Integrations, yes — every generated worker draws on thousands of ready integrations (SAP, Oracle, Workday, Salesforce, ServiceNow and more), with human-approval workflows, monitoring, and tests in the box.
There is no predefined catalog to outgrow — every worker is generated fresh from your context, and its blueprint is readable before it runs.
Rehearsed before it touches anything real.
Workers rehearse on the Simulated Enterprise — a complete synthetic company with customers, tickets, email, and chat. Compress weeks of business events into minutes and attack your workers the way adversaries will, before go-live.
Replay any change against identical scenarios: same input, same governed path, same auditable output.
Export the code. Run it without us.
Production comes only after rehearsal and your approval gates — then you export complete, production-grade source code to your infrastructure. No vendor runtime. No per-decision billing. No calls home.
Every export ships the Ownership Audit, and exports are byte-for-byte reproducible — the code you audited is provably the code you deployed.
See the code-quality bundle on the Trust CenterThe Nexgile difference.
Frontier models are interchangeable. The Foundation is the layer every Nexgile digital worker stands on — four named mechanisms that turn claims you would otherwise have to trust into things you can read, replay, or run yourself.
Rehearsed on a complete synthetic company.
A complete synthetic company in every workspace — customers, tickets, email, chat — so digital workers rehearse real work before they touch a live system. Compress weeks of business events into minutes, attack your workers the way adversaries will, and replay any change against identical scenarios to see exactly what improved. Rehearsal runs on synthetic data only — no production data in simulation, preview, or red-teaming.
Routine decisions never call the model.
Routine business decisions don’t need AI to re-think them. When a worker is built, the platform compiles them once into deterministic rules that run instantly, identically, and at zero AI cost for the worker’s entire production life. Live judgment is reserved for the genuinely novel cases — and a compiled rule can’t be talked out of policy by a clever prompt.
Your auditors read it before it runs.
Every digital worker is a readable, versioned blueprint, not a tangle of prompts: what it does, who approves what, where it escalates. Diff it when policy changes, test it like code, trace exactly which version ran when, and hand it to your auditors — they read what the worker will do before it does it. The blueprint is the audit artifact, and like everything the platform generates, it’s yours.
Verify the no-lock-in claim yourself.
Every export includes verification tooling your own engineers run against the delivered code. It scans for vendor dependencies, calls to Nexgile domains, and license checks. Run it on your hardware, without trusting us — the verdict is yours to read, and a sanitized sample of its output is available on request via the Trust Center. Pair it with byte-for-byte reproducible exports, and the code you audited is provably the code you deployed.
AI judgment backed by verifiable rules — explainable, auditable, regulator-ready. Workers score their own confidence against thresholds you set; below-threshold cases must route to a human — the worker cannot proceed alone.
Watch a digital worker decide.
Most of what a worker does all day isn't judgment — it's policy. The engine separates the two when the worker is built: policy becomes compiled rules, genuine judgment goes to AI under budgets you set, and anything uncertain goes to your people.
Nine decisions queued from the worker's inbox.
Compiled rules
Instant. Identical. The model is never called.
Live AI judgment
Genuinely novel cases — under hard budgets you set.
Human review
Below your confidence threshold — a person decides.
Illustrative scenario — one accounts-payable worker. Your routing mix depends on the workforce you design; what never changes is the construction: rules never call a model, judgment is always budgeted, and uncertainty always reaches a person.
Routine decisions cost zero AI tokens — not discounted, never billed: the model is simply never called. The only AI spend left is the genuinely novel work, capped by budgets you set.
How our pricing worksNo drift, no moods, no “it answered differently today.” The same input takes the same path to the same answer — and when policy changes, you replay the same day to see exactly what changed.
A compiled rule can't be talked out of policy by a clever prompt. Every decision lands on a tamper-evident audit trail, and anything below your confidence threshold must go to a human.
Read the Trust CenterThe blueprint is the audit artifact.
Every digital worker is a Declarative Agent Blueprint: your business logic captured as a readable, versioned artifact — its agents and roles, integrations, human-approval gates, routing and decision rules — not buried in prompts and not trapped in a vendor's runtime.
- Intake: refund requests from email and chat
- Check: order history, payment record, prior refunds
- −Approval: refunds route to one reviewer
- Escalate: below-threshold confidence routes to a human
- Intake: refund requests from email and chat
- Check: order history, payment record, prior refunds
- +Approval: refunds above a limit require dual sign-off
- Escalate: below-threshold confidence routes to a human
Illustrative. One artifact serves three audiences at once: your engineers version and diff it like code, your governance team reads it before deployment, your auditors verify against it after. Blueprints are testable before they ever run and portable across your choice of language, framework, and cloud — generation that produces an asset you own, not a tenant configuration you rent.
Whichever seat you're in.
Move from managing people to orchestrating outcomes.
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Outcomes, not infrastructure
Describe the work in plain language and get a team of digital workers — and the software to run them — built for your business.
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Proof before production
Watch workers rehearse on the Simulated Enterprise and evaluate accuracy, cost, and safety before a single real record is touched.
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Own what you run
100% ownership, self-hosted, no per-decision billing. The economics of software you own — not metered SaaS.
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Built for regulated industries
Explainable, auditable, repeatable decisions — our work concentrates where the bar is highest: finance, healthcare, insurance, and the public sector.
Ship faster with an agent that thinks in your codebase.
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An agent in your editor
Nx IDE plans, builds, tests, reviews and ships — a team of 30+ specialists coordinated end to end.
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Any model, your choice
Bring the AI providers you already trust, including private and on-device models. Right model for each job, no lock-in.
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Control you can defend
Granular approvals, allow/block lists, spend caps, protected files and instant rollback — speed inside boundaries you set.
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Workers as blueprints
Digital workers are Declarative Agent Blueprints, not brittle prompts — testable, versionable and portable across your stack.
Read what a worker will do before it does it.
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Read the blueprint before deployment
Every approval, threshold, and escalation path is legible in advance. Dual sign-off is enforced for regulated work — at design time and at runtime.
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Tamper-evident decision lineage
Every action lands on a tamper-evident audit trail with full decision lineage — the audit-trail specification is available to your auditors via the Trust Center.
Read the audit-trail specification entry -
Provably the code your auditors reviewed
Exports are byte-for-byte reproducible, so the code your auditors reviewed is provably the code deployed.
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Evaluation without data sharing
Rehearsal runs on synthetic data only — a description-based evaluation needs no data-sharing agreement, so your security team can say yes on day one.
Your AI bill shouldn't be a weather forecast.
Metered platforms bill you every time your worker thinks. Ours compiles the thinking you've already done. You watched it happen above: routine decisions run as compiled rules that never call a model, so the only AI spend left is the genuinely novel work.
The AI judgment that remains runs on right-sized models under hard budgets you set, with every call attributed, capped, and stoppable within a minute, and the worker's projected cost profile visible in the preview before you deploy.
Because you export and run the code yourself, there is no runtime license and no per-decision meter — as your workforce scales, there is no Nexgile meter scaling with it. Success never raises what you pay us.
AI tokens for routine decisions
By construction, not by discount — for the worker's entire production life.
Hard budgets you set
Every live AI call attributed, capped, and stoppable within a minute — and the projected cost profile is visible in the preview.
Success never raises what you pay us
You export and run the code yourself: no runtime license, no per-decision meter, no Nexgile meter scaling with your workforce.
Our business model is the proof. We charge to design your workforce, not to run it. A vendor with a meter profits when you depend on it; our incentives point at your independence — ongoing help is optional, on your terms.
How our pricing worksTwelve questions to ask any digital-workforce vendor — including us.
Take this list into every evaluation. We wrote it because we're comfortable answering all twelve.
Can your auditors read what the worker will do before it runs — or only watch dashboards after?
If you cancel, what keeps working?
Can you export the source code — all of it?
Is there a per-decision meter, and what happens to your bill when volume doubles?
What happens to routine decisions when the model misbehaves?
Can a clever prompt talk the worker out of policy?
Is the demo the same code as the deployment?
Can you rehearse the worker against realistic work before connecting a live system?
Does evaluation require sharing production data?
Who approves what — and is approval enforced in the code, or in a setting?
Can you verify the no-lock-in claim yourself, on your own hardware?
Does every number in the pitch come with how it was measured?
Our answers are on this page.
What the words mean.
Nexgile is the owned digital workforce platform. Three terms carry precise meaning here:
Digital worker
A complete, owned software system that staffs a process — not a hosted bot.
Blueprint
Your business logic as a readable, versioned artifact your auditors can review before it runs.
Export
Production-grade source code that runs on your infrastructure, without us.
Sample repo tree, runbook page, and test-and-coverage reportWhitelabel-ready applications, generated and delivered.
Generated, governed software workers — delivered as owned source code.
Specialist designs for finance, healthcare, legal, supply chain, HR, retail and manufacturing.
Portal and worker counts from our delivery records, verified June 2026. A digital worker is a generated, governed software worker delivered as owned source code — not a rebadged bot or script.
Three ways to work with us.
Managed Delivery
End-to-end design and delivery of your digital workforce — we run the build, you own everything we ship.
Bespoke Agentic Engineering
Specialist teams that design, build, and extend agentic systems — and the software around them — scoped to your roadmap.
Strategic Staffing
Senior engineers and AI specialists embedded with your teams, augmenting capacity on your terms.
You generate it. You preview it. You own it. You run it.
See the platform design, rehearse, and deliver a digital workforce — live, on the Simulated Enterprise.