Document intelligence and RAG
For teams that need accurate, sourced answers from internal documents, playbooks, and business knowledge.
- Document ingestion and curation
- Answer accuracy and source attribution
- Evaluation and response quality checks
Building the last mile of Enterprise AI.
Most AI projects stall at the chat interface. We implement the underlying architecture — connecting Amazon Bedrock to your document knowledge and business actions with absolute governance.
01. Structured Insight
Metrics & operational data prepared for reliable answers.
02. Document Context
Answers sourced from policies, SOPs, and knowledge.
03. Governed Action
Tasks, routing, and controls around who can do what.
Powered by Amazon Bedrock, Quick Suite & RAG
Core Services
Operational AI on AWS
From document intelligence to governed automation, we build systems meant to be used inside real operating processes.
Workflow automation
For teams that want AI systems to trigger or coordinate work, with clear controls over tools, actions, approvals, and fallbacks.
Amazon Quick Suite implementations
For teams that want analytics, policy-backed answers, and action paths inside a single operational workflow on AWS.
- Operations and finance workflows
- QuickSight-ready data modeling
- Role-aware actions and routing
Reference Implementation
Finance operations workflow
We engineered this finance operations workflow end-to-end to validate the architecture before offering it to our clients. It serves as a production-grade benchmark for how data, policy, and action intersect in a single operating model.
Domain
Overdue invoices, exception handling, and follow-up review workflows.
Roles
Manager, Analyst, and Administrator with visible differences in access and action rights.
Flow
Question from data, answer from documents, then route a task with governance controls.
Data Finance dataset
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Interface Quick Suite workflow
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Knowledge Policy document pack
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Action Follow-up task routing
How we work
What a first project looks like
01
Choose one workflow
Pick one business process where data, documents, and actions already intersect. We focus on clarity over scale initially.
02
Model the inputs
Prepare the dataset, the document collection, and the action path before focusing on interface design.
03
Ship the governed path
Make the output operational, with role-aware controls and a clear end state. No theoretical models.
04
Define the next phase
After the first project, you will have a clear picture of whether to expand the workflow, integrate further, or leave it as-is.
Start small,
evaluate clearly.
If you already know the workflow you want to pilot, we can validate the scope. If not, we can help narrow it to one practical use case.
Book a 30-min call →Direct Contact
info@arvenik.ai