Blog14 min read
LLM-Based Document Processing vs Traditional OCR: When Each Actually Belongs in Your Stack
Compare OCR and LLM document processing: speed, cost, accuracy, and when to use OCR, LLM, or a hybrid pipeline.
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Blog
Notes from the build.
Field notes on shipping AI-native systems with human engineering judgement: architecture, modernisation, automation, and the tradeoffs in between.
Blog19 min read
RAG Implementation Checklist: 12 Things to Validate Before Going Live on Enterprise Documents
12 validation checks to ensure enterprise RAG systems are accurate, fast, secure, and cost-effective before production.
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Blog15 min read
On-Device AI With SLMs: The Latency and Memory Trade-offs Nobody Benchmarks Honestly
Why on-device SLMs often fail in practice: hidden memory spikes, thermal throttling, long load times, and heavy battery use.
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Blog18 min read
How to Identify Which AI Features in Your Product Can Be Served by an SLM Without Degrading UX
Learn how to audit AI features to move predictable, high-volume tasks to small language models without harming UX.
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Blog17 min read
The GPT-4 to SLM Migration Decision: When Smaller Models Are Good Enough and When They Will Cost You
Match models to tasks to cut AI costs-use SLMs for structured, high-volume work and reserve GPT‑4 for complex or multilingual cases.
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Blog18 min read
Why Enterprise Clients Are Now Asking for SLM Options Before Signing Off on Any AI Feature
Enterprises require SLMs for data sovereignty, compliance, security, and cost savings; vendors must offer self-hosted, VPC, or on‑prem options.
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Blog23 min read
Self-Hosted SLMs for Regulated Industries: Architecture, Cost, and Compliance Trade-offs We’ve Navigated
Architecture, cost, quantization, and compliance trade-offs for self-hosting language models in regulated industries.
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Blog12 min read
Phi-4 vs Gemma 3 vs Mistral Small: A Practical Benchmark for the Enterprise Use Cases That Actually Matter
Pick the right enterprise LLM by matching precision, context length, and throughput to your workflow.
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Blog15 min read
How to Stress Test an Agent Framework Before You’re Too Deep to Switch
Stress-test agent frameworks early: add observability, reproducible tests, run five critical stress tests, and know when to switch.
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Blog20 min read
The Hidden Complexity in Multi-Agent Orchestration That Every Demo Skips Over
Why multi-agent systems fail in production: deadlocks, cascading errors, context loss, poor observability, and exploding token costs.
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Blog16 min read
Agent Memory Architecture: Why Your Design Decision at Week One Determines Your Ceiling at Scale
How week-one memory choices set an AI agent’s scalability; compare in-context, vector, episodic, semantic memories and tiered designs.
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Blog17 min read
Tool Calling Reliability Across Agent Frameworks: What We Measured and What It Means for Your Architecture
Tool-call failures compound in multi-step agents; robust architecture, deterministic routing, and strict validation are the real drivers of production reliability.
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