How our contracts are structured
AI tools, custom agents and machine-learning workflows built around your existing systems, in your cloud or on your own machines. Discovery and a quick prototype are free. If the idea is useful, we agree a price to build and deliver it.
Start with one repeated task or a process your team wants to improve. We can work directly with a small business or alongside your engineering and cloud operations team. You choose a managed product or a system that runs in your own environment.
What we build
Practical workflows we can build around your business. These are examples, not client case studies:
Manuals and support answers
KnowledgeSearch approved manuals and product information, then prepare answers with sources your team can check.
● try the live demo →Enquiries ready to quote
SalesTurn customer messages into a clear brief, flag missing specifications and draft clarification questions.
Shipment document processing
OperationsExtract agreed fields from shipment documents into a review sheet or your existing workflow.
● try the live demo →Print and artwork briefs
SalesPrepare quotation checklists from customer requests, leaving artwork approval, product choices and pricing with your staff.
Equipment hire enquiries
ServiceOrganise requirements and draft follow-ups so your team can check suitability and availability.
Order and shipment updates
OperationsPrepare status replies using approved order information, with staff reviewing messages before they are sent.
Custom agents and workflows
AgentsConnect AI tools to the documents, software and data your business already uses, with clear permissions and review points.
PII redaction and data safety
SafetyIdentify personal information in documents and review proposed redactions before sharing them.
● try the live demo →AI guardrails
SafetyAdd screening, evaluation and human approvals around the inputs and actions of your AI workflows.
● try the live demo →Custom machine learning
ModelsExplore forecasting, anomaly detection or model training using suitable business data and agreed evaluation criteria.
● try the live demo →Document intelligence
LanguageExtract, classify and search your paperwork, from cited answers to tables you can review and use.
● try the live demo →Reading scanned archives
LanguageTurn scans and photos into text for a searchable archive or another business workflow.
● try the live demo →What it costs
From A$1,000
A small project, with the scope and price agreed before production work starts
A simple offline agent starts from A$1,000. A small custom workflow is around A$2,000, and focused custom model work is typically A$2,000–4,000. These are indicative prices in Australian dollars; your quote confirms the scope, tax treatment and separate costs.
Discovery and a quick prototype are free
We discuss the task and agree a small demonstration using suitable sample material. You can see the idea in action before deciding whether to fund a production build. The discovery chat and scoped quick prototype cost nothing and carry no obligation.
Data preparation, integration needs and testing affect the final scope. Model training and architecture work beyond a small project are quoted separately.
What you provide
We agree the material, access and environment needed for your project before paid work begins.
Your data and workflow
Bring an example of the task and suitable sample material. During discovery we agree what information is needed, who can access it and how to evaluate the result. If the data is not ready, we will identify that before quoting production work.
Your systems and infrastructure
We agree how the tool connects to your software and where it runs. Hardware, hosting, model/API usage and any external services are identified in the quote. For an offline deployment, your team provides and operates the agreed local environment.
From discovery to delivery
Start with one useful idea, try it, then decide what to build. Timing is agreed for each project.
- Step 01
Discovery chat — free
Show us a task you want to improve and the systems your team uses today. We explore where AI could help and agree what a useful demonstration would show. The conversation is free and carries no obligation.
- Step 02
Quick prototype — free
We agree one small concept to test using suitable sample material. You can try the idea before deciding whether a paid build makes sense. The prototype is a demonstration; production integrations, testing and deployment belong to the subsequent paid scope.
- Step 03
Agree the scope and build
If the prototype is useful, we quote the deliverables, success criteria and delivery plan. Once you approve the proposal, we build the workflow and evaluate it against the agreed examples.
- Step 04
Deploy in your environment
Choose a managed product or a deployment your team operates. We connect it to the agreed systems, test it with your team and complete the documented handover. Timing and ongoing support are agreed for your project.
Choose how it runs
After the paid build, choose a managed service or deployment in your own environment.
Managed: A$20–40 / month
An optional managed product for a small, agreed workflow. The monthly fee excludes usage and is separate from custom build and integration costs. Hosting, support and usage arrangements are confirmed in the proposal; larger workloads are scoped individually.
Offline: no ongoing subscription
After the paid build, the delivered system runs in your environment without a recurring Edge Attention subscription. Suitable tasks can run fully offline when the models and data are local. Your hardware, external services and future support or changes remain separate where needed.
Scope and price agreed up front
The proposal sets out the deliverables, success criteria, integrations and responsibilities. It confirms the price, any applicable tax and separate running costs before production work begins.
Evaluation and handover
We test the agreed workflow using representative examples, deploy it in the chosen environment and provide the agreed documentation and walkthrough. Your team knows how to review the output and operate the system.
When it is bigger than this
Broader AI/ML stacks, multiple integrations, extensive model training or work alongside your cloud operations team need a separate scope. We can help with architecture, deployment, access controls, evaluation and monitoring within your environment.
These projects are quoted after discovery. We agree the deliverables, responsibilities, infrastructure, usage costs and support arrangements before production work begins, so your team can decide what to take forward.
Want to explore the capabilities? Try our browser demonstrations, then bring us a task you would like to improve.