LiquidAI LFM2.5-2.6B: On-Device Reasoning and Native Tool Use Under 2.5 GB
Introduction: The Shift Toward Local, Privacy-First AI For the past three years, the dominant paradigm in artificial intelligence has been cloud-centric: centralize... Read more.
Deterministic Control Over Non-Deterministic AI: Why Production Agents Demand PydanticAI and LangGraph
In production services relying on raw string interpolation, unhandled execution faults stem directly from four output failure modes: dropped mandatory payload keys,... Read more.
Building a Closed-Loop RAG Flywheel: Operationalizing Expert Feedback to Reduce Hallucinations
Standard Retrieval-Augmented Generation (RAG) pipelines often encounter quality ceilings in production. While synthetic benchmarks and evaluation frameworks like... Read more.
Beyond Pure Vectors: Implementing High-Precision Hybrid Search Natively inside Postgres
We observed a 500ms synchronization lag when separating our storage engine from an external search cluster, which causes broken user experiences when resolving exact... Read more.
Start Fresh, Don’t Lift and Shift: Scaling Analytics Platforms with dbt-core and PostgreSQL
We observed that executing a “lift and shift” of legacy, sprawling SQL scripts onto an enterprise cloud data warehouse fails to resolve core structural... Read more.
PostgreSQL Data Mesh: A Technical Guide to Schema Segmentation, Boundaries, and Governance
We deploy PostgreSQL natively to execute a decentralized data mesh architecture, proving that multi-million dollar cloud platforms and proprietary vendor ecosystems... Read more.
Deterministic RAG Auditing: Implementing Verifiable Grounding & Lineage on Unified PostgreSQL
The pervasive “lost in the middle” phenomenon is a failure of semantic retrieval, not just context window capacity. While increasing token limits is... Read more.
Beating “Lost in the Middle”: Unified Graph RAG on PostgreSQL
Our evaluation shows that by substituting naive chunk-based vector lookups with relationally injected context, the model’s $F_1$ verification score increased from... Read more.
RAG Context Pruning for Efficiency and Cost Optimization
After baseline production runs across our clients’ financial discovery pipelines, we observed an increase in Time-to-First-Token (TTFT) when retrieved context... Read more.
Production-Grade Compliance: Engineering the EU AI Act into Sovereign Agentic Pipelines
We measured a 42% increase in inference latency when we shifted from standard RAG to a cryptographically-verifiable audit chain. We accept this overhead. After 2,000... Read more.