Evaluating AI Agents: What to Measure Before Production
Agent demos impress; production agents must be measured. A practical framework for evaluating AI agents before they touch real workflows.
- Task success measurement
- Tool discipline measurement
Engineering Enterprise AI Beyond the Hype.
Practical thinking on building, securing, evaluating and operating AI systems in real enterprise environments.
Agentic AI
Human-in-the-Loop Architecture for Enterprise AI Agents
Where humans stay in the loop for enterprise AI agents: approval gates, escalation design, confidence thresholds and decision boundaries boards can defend.
- Three loop patterns
- Approval gate design
AI Agents vs Traditional Workflow Automation
Where deterministic automation ends and agentic reasoning becomes useful — a practical guide for enterprise teams choosing between the two.
- Architecture comparison
- Security, governance and operations
Enterprise RAG
How Permission-Aware RAG Works
Enterprise RAG must enforce document permissions at retrieval time. How permission-aware retrieval works, why post-filtering fails, and how to architect it.
- Permissions from the start
- Permission-aware retrieval
Why Enterprise RAG Projects Fail in Production
A successful RAG prototype does not automatically become a reliable production system. Real enterprise deployments must address permissions, source quality, document freshness, retrieval performance, evaluation, observability and governance.
- Source data quality
- Retrieval-time permissions
Document Intelligence
From Invoice OCR to Intelligent Accounts Payable
How OCR becomes extraction, validation, exceptions, approvals and integration — the path from reading invoices to an intelligent AP workflow.
- Invoice ingestion
- Classification and structured extraction
AI Engineering
MLOps vs LLMOps vs AgentOps: What Changes and What Does Not
MLOps, LLMOps, and AgentOps share a lineage but solve different problems. When your organization needs each discipline — and what carries over.
- MLOps foundations
- LLMOps and AgentOps
AI Security
Document AI Security: Keeping Sensitive Data Out of Model Training
Document AI systems see your most sensitive files. Here is how to keep them out of model training and retained logs.
- Training-data protection
- Data residency and processing
Enterprise AI
The Total Cost of Enterprise AI: Beyond API Bills
Model API spend is the smallest line item. The real cost of enterprise AI is data, integration, evaluation, operations, and governance.
- Inference costs
- Data and integration costs
Discuss Your AI Workflow
Describe the process. AISoltrics will review the workflow and explore whether AI or automation is a practical fit.
Discuss Your AI Workflow