AI JobsStart a program

AuraOne / Enterprise Intelligence

Turn the work you repeat into intelligence you own.

One workflow. One definition of done. AuraOne runs the work, routes exceptions to the right people, and remembers every accepted result.

Every run keeps the work, the judgment, and the proof connected. So the next version starts with everything the last one learned.

Show us the workBecome a design partner
Input
Show us one recurring workflow and the result it needs to produce.
Output
A finished workflow result, plus a versioned task model and scoped endpoint when the task qualifies.

Enterprise Intelligence

Two ways to put Enterprise Intelligence to work

Start with the workflow, inputs, systems, business rules, and acceptance criteria. AuraOne can own the operation first, then specialize a task model when the evidence supports it.

01 / Managed workflow

Managed Workflow

Send us the work. Get the finished result.

AuraOne operates the workflow with software and qualified people where judgment is required. You receive accepted outputs, exceptions, review history, and measurable operating results.

  • Workflow, files or records, business rules, and acceptance criteria
  • Completed work, exception record, and acceptance evidence
  • Cost, quality, turnaround, and retained corrections
InputWorkflow + records + criteriaCompleted work + evidence
Scope a managed workflow

02 / Dedicated task model

Dedicated Task Model

Turn the work your team already accepts into intelligence trained for that task.

When volume, repeatability, data rights, and a measurable quality bar support it, AuraOne creates a task-specific model, proves it against a held-out baseline, and deploys it through a scoped endpoint or approved integration.

  • Accepted examples, corrections, failure cases, and evaluation criteria
  • Task dataset, candidate model, evaluation results, and regression suite
  • Versioned deployment endpoint or approved enterprise integration
Model runs behind AuraOne-managed operationApproved customer-system integration

Dedicated training begins once the task, rights, data volume, and baseline are established. Model and downstream rights are defined in the applicable scope.

Scope a task model
Managed workflows can become the data engine for dedicated task models.They are connected paths, not an automatic promise: enough clean, rights-cleared signal and a repeatable task boundary are required.

The handoff stays scoped

Show the input. Show the output. Then choose how it runs.

These are representative workflow shapes, not prebuilt vertical products. The selected job keeps the same required result in a managed operation or a scoped system integration.

Choose a category

8 workflows in Featured

Choose the delivery

Choose a workflow

Browse the recurring jobs that fit this category. The selected job keeps the same required result in either delivery mode.

Featured

Managed workflow

Product Catalog

Managed

Normalize product facts, options, and attributes before they reach the merchandising system.

InputSupplier PDFs, spreadsheets, websites, and images
OutputComplete structured product records ready for the catalog
Managed

Send the supplier sources to AuraOne. We normalize the product facts and return catalog records ready for merchandising review.

The compounding data loop

The system remembers what worked.

Accepted results become proof. Approved corrections become tests. The next version begins where the last one finished.

  1. 01

    Customer workflow

    The repeated job, inputs, rules, examples, and acceptance bar.

  2. 02

    Governed execution

    The approved workflow version runs with permissioned context, models, tools, budgets, and action policies.

  3. 03

    Human exception

    Uncertain or sensitive cases pause durably for qualified review, QA, or adjudication before the same run resumes.

  4. 04

    Delivered outcome

    The result ships with its manifest, trace summary, exceptions, rights scope, and acceptance standard.

  5. 05

    Acceptance + economics

    Accept, reject, or request rework. Contract-defined acceptance can create usage, invoicing, and expert earnings exactly once.

  6. 06

    Incident + replay

    Failures and rejections retain the evidence needed to replay the run without repeating external side effects.

  7. 07

    Regression memory

    Rights-cleared corrections and production failures become permanent cases the next version must pass.

  8. 08

    Release gate

    Historical, edge, adversarial, tool, human, cost, and latency evidence produces a ship, hold, reject, or rollback decision.

New failure returns to review, correction, and the next training / regression record.

More than a model. A system that can do the work.

AuraOne connects the workflow, its rules, its tools, its reviewers, and its evidence into one versioned system.

  1. 01

    Define it

    Lock the input, output, rules, context, tools, budget, and definition of correct into one approved version.

    Approved workflow version

  2. 02

    Run it

    Let AI do the repeatable work. Keep every read, action, approval, and external receipt attached.

    Tool calls and side-effect receipts

  3. 03

    Review it

    When judgment matters, pause for the right person. Give them the evidence, the policy, and a clear decision to make.

    Review, QA, adjudication, and correction

  4. 04

    Improve it

    Turn accepted outcomes and approved corrections into evidence the next version must learn from and tests it must pass.

    Trace, replay, regression, and release gate

Operating trace

Deploy the intelligence where the work already lives.

The delivery choice changes the handoff, not the job. AuraOne can operate the workflow, or scope an endpoint and approved integration around your systems, security requirements, and operating environment.

  1. 01

    Your input

    Documents, records, code, conversations, images, system data, or another defined input enter the workflow.Customer systems and rights

  2. 02

    AuraOne-built task intelligence

    A managed workflow or task-specific model produces the required result.Versioned system and criteria

  3. 03

    Delivery boundary

    AuraOne runs the work, or the customer's operation calls the scoped task-model deployment.Operating ownership

  4. 04

    Result and review state

    The output, confidence or exception state, review record, and version stay connected.Delivery and evidence record

Operating flow

Each checkpoint moves the work forward with a clear owner, review, and next step.

  1. 01

    Watch

    Understand how the work actually happens, including exceptions and human judgment.

    Workflow baseline

  2. 02

    Run

    AuraOne performs the workflow using software and qualified people where needed.

    Completed work units

  3. 03

    Accept

    The customer accepts or returns outputs against explicit criteria; exceptions stay attached.

    Accepted outcomes + exceptions

  4. 04

    Train

    Where the task qualifies, accepted outcomes and corrections become training and evaluation signal for a dedicated model.

    Training set + candidate model + evaluation

  5. 05

    Compound

    More repeatable work moves into software or model execution; hard cases stay in the review loop.

    Quality, coverage, cost, and turnaround by version

What you receive

What your team receives

The completed work, the information needed to review it, and a clear next step stay together.

Workflow
The recurring job, its owners, and the exceptionsApproved workflow baseline
System
The task-specific AI, surrounding software, and versionVersioned workflow system
Quality
The acceptance criteria, test cases, and production correctionsApproved evaluation and regression record
Deployment
Managed operation or scoped task-model handoff in the agreed environmentDeployment and ownership record
Result
The finished output, exception state, and review recordTenant-scoped delivery record
Intelligence
When task-model scope applies: model version, training/evaluation record, deployment configuration, and regression historyScoped task-model package

What your team can do next

Connect the completed work to the decision, handoff, or release it supports.

What your team can do next. Connect the completed work to the decision, handoff, or release it supports.
OutcomeWorkWhat you receiveProgram fit
You get the finished workflow resultAuraOne defines the accepted result, runs the task-specific workflow, and proves it against real work.Versioned workflow, baseline comparison, accepted outputs, and exception record.Each engagement covers one named workflow and its approved systems, data, and actions.
You choose the operating pathSend AuraOne the work for a managed result, or scope a task-model endpoint / approved integration when the boundary is ready.Delivery mode, deployment boundary, result contract, and exception state.Endpoint and integration availability depend on qualification, security review, and the agreed deployment scope.
Accepted work can become task intelligenceWhen volume, repeatability, rights, and acceptance criteria support it, approved outcomes and corrections become training and evaluation signal for a dedicated model.Task dataset, candidate comparison, regression history, and measured versions.Training or specializing a task model is scoped separately; weights/checkpoint and downstream rights depend on the base model and contract.

Related paths

Continue into the supporting product or documentation.

Model ImprovementTurn accepted outcomes, expert corrections, and failures into a stronger task model.Workflow Design PartnersBring one workflow. Start managed, then graduate to task intelligence when it qualifies.DevelopersReview the current API, SDK, webhook, and deployment boundaries.