AI Automation That Solves a Real Problem — Not a Demo
We design and implement AI agents and automation workflows that remove manual work from your finance, operations, and customer processes — scoped precisely, tested against your data, and managed by Datavaura end to end.
Business Problem
Most AI conversations stay theoretical. Businesses are told they need AI agents without a clear answer to which process it should touch, what data it needs, or how it fails safely. We start with one specific, high-friction process — invoice processing, lead routing, reporting, customer follow-up — and build an automation or AI agent that removes the manual work from that process, tested against your real data before it touches a live workflow.
What Datavaura Does
Process discovery — identify where manual work is highest-friction and most repetitive
AI agent design — scoped to a specific task with defined inputs, outputs, and failure handling
Workflow automation — connecting existing systems so data moves without manual re-entry
Retrieval-based lookups (RAG-style) so an agent references your own documents and records accurately
Integration with ERP, CRM, email, and reporting systems already in use
Testing against real (anonymized) data before production use
Documentation and handover — how the automation works and how to adjust it
Platforms supported: OpenAI and Anthropic APIs · Microsoft Power Automate · Zapier and Make · Python-based agents · Copilot Studio
Typical Deliverables
- Signed Statement of Work with defined process scope and success criteria, subject to agreed scope and SLA
- Process map — before and after
- Working automation or AI agent, tested against real data
- Exception-handling and guardrail documentation
- Handover documentation and short training session
Who Is This For?
Finance teams doing manual reconciliation or data entry. Operations teams handling repetitive administrative tasks. Customer service teams needing faster first-response handling. Businesses that have looked at AI but don't know where to start.
* In scope: Process discovery, agent design, build, integration, and testing under Datavaura oversight, plus documentation. Out of scope: Training/fine-tuning foundation models, general data science research, ongoing monitoring beyond the agreed SLA (available under Managed IT).
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