AI Insights & Technical Blog

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Featured • 12 min read

Why Recursive Character Splitting Fails for Legal Clauses

The default chunking logic in most AI orchestration frameworks works well for blog posts and general knowledge bases. But it's a disaster for legal contracts, where a single clause can span 3 pages and reference definitions from 50 pages earlier.

In this deep-dive, we explore why semantic chunking outperforms naive splitting for legal documents, and share our custom "clause-aware" algorithm that increased retrieval accuracy by 47% in a recent law firm deployment. We cover how clause boundaries, cross-reference preservation, and definition-linking transform retrieval quality from "generally correct" to "courtroom-ready."

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Jan 8, 2026 • 8 min read

Deploying a Private LLM in a HIPAA-Compliant VPC

Healthcare and biotech companies face a unique challenge: leveraging AI while meeting strict HIPAA requirements. This step-by-step DevOps guide walks through deploying a fully private LLM inference endpoint on AWS—from VPC network isolation and encryption at rest to audit logging and BAA compliance. We cover the entire stack: compute selection, model serving, API gateway hardening, and automated compliance checks that run on every deployment.

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Jan 3, 2026 • 6 min read

The True Cost of "Free" AI: Why Public SaaS Is Expensive

That $20/month AI subscription might be costing your firm $200,000 in data leakage risk. When employees paste confidential legal briefs, patient records, or M&A documents into public AI tools, the real cost isn't the subscription—it's the regulatory exposure, IP leakage, and reputational risk. Here's the math most CTOs ignore, and why a private deployment often costs less than the liability of doing nothing.

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Dec 28, 2025 • 10 min read

Choosing Your Vector Database: Purpose-Built vs. Postgres Extensions

When should you use a purpose-built vector database, and when is a Postgres extension "good enough"? We benchmarked both approaches across 3 production deployments with real enterprise workloads—50K+ documents, concurrent queries, and mixed embedding dimensions. The results might surprise you: purpose-built wins on speed, but Postgres extensions win on operational simplicity. We break down exactly when each option makes sense for your use case.

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Dec 20, 2025 • 7 min read

Re-Ranking: The Secret Weapon Against Bad Retrieval

Your semantic search returns 20 documents. Only 3 are relevant. The problem isn't your embeddings—it's that you're missing a critical second pass. Re-ranking models act as a precision filter after initial retrieval, re-scoring each result with cross-attention against the original query. In our testing across legal and pharma deployments, adding a re-ranking step improved answer accuracy by 35% without changing anything else in the pipeline.

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Dec 15, 2025 • 9 min read

From SharePoint Chaos to Searchable Knowledge

A mid-size consulting firm came to us with 8 years of orphaned SharePoint sites, 3 different naming conventions, and zero documentation structure. 200 consultants were spending an average of 45 minutes per day searching for internal documents. This case study covers how we untangled the mess: automated content classification, deduplication pipelines, and a unified AI-powered knowledge base that cut search time by 82%.

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Dec 10, 2025 • 5 min read

Infrastructure-as-Code for Enterprise AI Deployments

Deploying an AI pipeline isn't just about the model—it's about the 47 other services that surround it: networking, secrets management, monitoring, logging, auto-scaling, and backup. Manual deployments introduce drift, security gaps, and "works on my machine" failures. We explain how Infrastructure-as-Code practices give you reproducible, auditable, and disaster-recoverable AI infrastructure—and why your security team will thank you.

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