KyperX AI

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Custom AI Systems

Develop AI around the problem, not the other way around.

When off-the-shelf software does not fit, KyperX develops AI-enabled products, internal platforms and specialised intelligent systems. The work progresses in stages, from technical discovery and prototype through evaluation, MVP and production engineering, so technical risk is reduced before larger investment is committed.

Discuss an AI System →Development stages ↓
Starting price
Initial development engagements from A$15,000 + GST
Production systems
Separately scoped
Stages
Discovery, prototype, MVP, production
Evaluation
On representative data, against agreed criteria

Outside Australia? Custom AI Systems with USD pricing →

Fit

When custom development is justified.

Custom development costs more than buying software. It is worth it when the problem genuinely needs it, and the first stage is there to establish that.

Justified when

  • The capability you need is not available as a product, or products do not fit your workflow, information or constraints.
  • AI is part of a product or service your organisation offers to its own customers.
  • The system has to work with specialised information only your organisation holds.
  • You need control over architecture, behaviour or deployment that a subscription product cannot give.

Not justified when

  • An established product already does the job adequately. We will say so.
  • The requirement is not yet defined. The AI Opportunity Assessment is a better first step.
  • The information the system would depend on does not exist or cannot be obtained.
  • A fixed price is needed for an undefined production system before any discovery.

What we build

Kinds of system KyperX develops.

Described by what the system does. These are areas of capability, not client references.

01

AI-enabled software

Products and platforms with AI capabilities designed in, including the evaluation, monitoring and interfaces needed to run them.

02

Specialised assistants

Assistants built around a defined task and a defined body of information, with limits on what they can access and do.

03

Decision-support systems

Systems that assemble evidence, analysis and options for a person who makes the decision, with sources that can be checked.

04

Computer vision

Image and video analysis for inspection, classification or measurement, evaluated on held-out samples from your own data.

05

Intelligent internal platforms

Internal systems that combine retrieval, automation and business logic around how a team actually works.

06

Integrated AI capabilities

AI components added to existing software, connected through bounded interfaces rather than rebuilt around.

Development stages

From technical discovery to production.

Each stage answers a question before the next is funded. Stages can be combined or skipped where the evidence already exists.

  1. 01

    Technical discovery

    What the system must do, for whom, with what information, under which constraints.

    Answers: is this worth building?

  2. 02

    Architecture

    Components, models, data flows, integration points and deployment position.

    Answers: how should it be built?

  3. 03

    Prototype and validation

    The riskiest technical assumption built and tested first, on representative data.

    Answers: does the core approach work?

  4. 04

    Evaluation

    Performance measured against criteria agreed in advance, with limits written down.

    Answers: is it good enough, and where does it fail?

  5. 05

    MVP

    A usable first version for real users, with the interfaces, integration and controls it needs.

    Answers: does it work in use?

  6. 06

    Production engineering

    Reliability, security, monitoring, scale, documentation and handover for ongoing operation.

    Answers: can it be run and maintained?

Engineering approach

How custom systems are built to last.

Delivery principles, not claims about completed client work.

01

Evaluation before features

Criteria and a representative test set are agreed early, so progress is measured rather than demonstrated.

02

Architecture for operation

Logging, monitoring, failure handling and change processes are designed in, not added after launch.

03

Data and deployment settled early

Where information comes from, where the system runs and what it may retain are decided before build decisions depend on them.

04

Documentation and handover

Designed so your team, or another provider, can understand, operate and change the system.

05

Ownership defined per engagement

Rights to custom deliverables, pre-existing components, third-party models and software are set out in the engagement agreement.

06

Technology chosen for the problem

Models, frameworks and infrastructure are selected against the requirements, and the reasons are recorded.

Scope and price

What is included, and what is scoped separately.

Prices in AUD, exclusive of GST. Scope and fee are confirmed in writing before each stage begins.

Initial development engagement

  • Technical discovery with the people who will own and use the system.
  • Architecture and technology recommendations, with trade-offs.
  • A focused prototype of the riskiest component, where scope allows.
  • Evaluation findings and an indicative plan for the next stages.

Scoped separately

  • MVP development and production engineering.
  • Large-scale data preparation, labelling or migration.
  • Hosting, cloud consumption, hardware and third-party licences.
  • Ongoing development, support or operation.

Have a system in mind?

Describe what it should do and why existing software does not fit. Early ideas are fine; discovery is part of the work.

Discuss an AI System →

Related

Where this connects.

Custom systems often draw on the other engagements and on capabilities described in depth elsewhere.

Questions

Questions about custom AI development.

What organisations ask before starting a build.

Can you build an MVP for a fixed price?

Once discovery and architecture have defined the scope and the main technical risks have been tested, later stages can be quoted as defined packages. Quoting a fixed price for an undefined system before that point would not be responsible.

Who owns the code and the system?

Ownership and licensing are set out for each engagement. Custom deliverables, pre-existing KyperX components, and third-party models and software are treated separately, and the agreement states which is which.

Which technologies do you use?

Those that fit the requirements. Model, framework and infrastructure choices are made during architecture, compared where it matters, and documented so they can be revisited.

What happens after the system is launched?

Handover includes documentation and knowledge transfer so your team can run it. Ongoing development, support or operation can be arranged separately.

What if the prototype shows the approach will not work?

Then the engagement has answered the question before larger investment was committed. The findings are documented, including whether a different approach is worth testing.

Enquiry

Discuss an AI system.

Describe the capability you need, who would use it and why existing software does not fit. Early ideas are fine; discovery is part of the work.

What happens next

  1. We review your enquiry. We read what you have described and check whether it is work KyperX can usefully do.
  2. We reply by email. Usually with a few questions, or a suggested time for a short conversation where there appears to be a fit.
  3. Scope is confirmed in writing. If an engagement is appropriate, you receive a written scope and fee before any work begins. There is no commitment until then.

Prefer email? Write to ai@kyperx.com.

Enquiry · Custom AI Systems · Initial development engagements from A$15,000 + GST

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