Business problem
Straight-through automation breaks on unstructured requests. Teams then move the exception back into inboxes and spreadsheets.
Services
AI Automation
Automation that combines rules, integrations, and language models where documents, messages, or requests need interpretation.
Solution
We separate deterministic steps from steps that need interpretation. Models are used where language varies. Rules, validations, and approvals remain explicit.
Capabilities
- Document and message intake
- Classification and routing
- Drafting for human approval
- System updates through existing APIs
- Exception queues
Benefits
- Less manual handling of repetitive requests
- Exceptions stay visible instead of failing silently
- Automation that can be explained to operators
Technologies
- Workflow engines
- APIs
- Document processing
- Model APIs
Implementation approach
- 01Measure the current manual path.
- 02Automate the predictable steps first.
- 03Add interpretation only where language varies.
- 04Keep a queue for cases the automation cannot complete.
Questions
How does an AI automation engagement start?
We start with a discovery conversation about the business problem, constraints, and what a useful outcome looks like. A written scope is agreed before delivery begins.
Can this be delivered with our internal team?
Yes. Work can be advisory, delivered by Curve Infotech, or shared with your team. The operating model is agreed during scoping.
Who owns the work product?
Ownership is defined in the statement of work. Commissioned deliverables are typically assigned to the client on payment, excluding pre-existing Curve Infotech tools and third-party software.
How is security handled?
Access, environments, and data handling are agreed up front. Production access is limited to what the engagement requires, and secrets are not stored in the application source.
Talk to our experts
Tell us about the business problem. We will reply with a scoped next step.