Document Processing: Validation is Plan A
Most document AI systems fail after extraction. This deep dive explains why validation breaks on an example invoice pipeline and how to fix it.
Document Processing isn't just Extraction
Document processing isn’t just LLMs and OCR. Learn how validation, normalization, and workflows make AI production-ready.
A Roadmap for CIOs to Turn AI Budgets into ROI
AI pilots stall before delivering value. This guide shows CIOs a six step roadmap to focus budgets on high-ROI workflows and measurable outcomes.
Why Most Generative AI Pilots Fail (and How to Be in the 5% That Succeed)
The State of AI in Business 2025 Report found that 95% of generative AI pilots fail to deliver ROI. This post summarizes the report’s findings and shares Agami’s perspective on how to design pilots that scale into production.
Unlocking the Potential: Top 3 AI Use-Cases in Commercial Lending
AI is no longer a pilot experiment. It is rapidly redefining how commercial lending teams assess risk, move files, and make decisions. For leaders who own credit quality and throughput, the question is how to harness AI to improve margin, control, and speed. Top 3 workflows that matter the most
Unlocking the Future: The Critical Importance of Private AI for Enterprises
Privacy is not a nice-to-have for regulated industries. It is the difference between experimenting with AI and deploying it into production with confidence. Leaders who own security, compliance, and uptime know the path to value looks very different when sensitive data is on the line. The enterprise AI fork: public
Distilling a High-Performance Language Model
How Agami turned a large, costly AI model into a lean, production-ready asset for enterprise use.
Context Engineering vs Fine-Tuning vs Distillation: How to Decide
Choosing between context engineering, fine-tuning, and distillation is key to making LLMs work in production. This guide explains each approach, when to use them, their trade-offs, and how to balance cost, accuracy, and scalability.
How AI Is Transforming Client Delivery for Market Research Firms
How AI helps market research teams scale client delivery with quality, consistency, and insight This is the fourth post in our five-part series on how AI is transforming key workflows in market research firms. In previous posts, we covered the big picture, business development, and knowledge management. “Can You Just
Context Engineering, Part 3: Making Context Work
What does it take to make Context Engineering work in production? In Part 3, we break down the platform components, team setup, key pitfalls, and the real tradeoffs between building your own stack or buying a platform like Agami.
AI for Knowledge Management in Market Research Firms
Market research firms amass vast insights, but poor discovery leaves them underused. AI-powered knowledge management democratizes internal expertise, enabling semantic search, AI summarization, and knowledge graphs that make insights instantly accessible.
How AI Helps Market Research Firms Win More Business
Solving the business development bottleneck with speed, context, and consistency This is the second post in our five-part series on how AI is transforming key workflows in market research firms. If you missed the first post on the big picture, you can read it here. The Proposal Is Due in