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Technical insights on LLM routing, AI evaluation, and scaling AI from prototype to production.
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60-second visual readsDivyam.AI: Analysis of competitive landscape
Most AI routing platforms handle requests and surface metrics. Almost none close the loop from observation back into automatic routing improvement. This paper examines why that gap matters and whether any competitor can close it.
EngineeringSwitching Models in a Day Is an Eval Problem, Not a Model Problem.
Open-source models caught up. Switching speed is the moat. The bottleneck isn't picking a model — it's continuously evaluating your prompt distribution against the next one. Here's what that actually means in production.
EngineeringWhat Open Weights Would Actually Do to Your Monthly LLM Bill.
Open-source LLMs list at 6-11x cheaper than frontier closed models on the price sheet. On a real bill, most teams capture 55-75% after the reasoning tail, tokenizer overhead, and migration work are in the model. Here's the math on a $60,000/month baseline.
Open SourceUnified LLM API: Introducing divyam-llm-interop for LLM API Translation
Every LLM provider speaks a slightly different dialect. divyam-llm-interop is our open-source unified LLM API (Apache 2.0): an LLM API translation layer that lets you switch models across providers without rewriting your integration.
EngineeringOpen Source LLMs Just Caught Up: Why Your LLM Router Needs to Switch in a Day
Lindy's founder said inference is now their #1 cost line, more than payroll. Open source LLMs just caught up on capability at 10-17x lower cost. The moat is no longer model choice — it's how fast your LLM router can switch.
StrategyWhat Divyam.AI Compounds for Your Business Over Time
What Divyam.AI compounds for your business over time: a control layer that keeps production aligned with the latest models, with cost and quality compounding as a side effect.
StrategySix Yes/No Questions That Reveal Your GenAI Product Maturity
A quick scorecard for engineering and product leaders. Six questions that reveal whether your GenAI product will hold up in production or quietly decay.
StrategyThe Six Capabilities Every Long-Running GenAI Product Needs
Most GenAI projects succeed in the demo and quietly fail in production. Here is the six-step quality flywheel that separates products that compound over time from ones that decay.
EngineeringHow to Reduce LLM Costs: The Hidden Cost of LLMflation and Model Inertia
LLM inference costs are falling 10x per year, but your LLM spend is growing. We modeled three approaches to reducing LLM costs on a $60K/month budget with 5% monthly growth. The gap between manual switching and per-prompt optimization is $333,000 per year.
EngineeringLLM Cost Optimization and AI Model Switching: The Model Inertia Problem
New frontier LLMs arrive every few weeks. Most production systems haven't switched models in months. That gap — Model Inertia — is the biggest blocker to LLM cost optimization, and it's getting expensive.
EngineeringTaking Your LLM Application to Production: What No One Warns You About
Building the first version of an LLM application is deceptively easy. Getting it to production — and keeping it there — is not. This post explores what it really takes.
ResearchLLM Router Comparison: Divyam.AI vs Microsoft Model Router vs NVIDIA LLM Router
How three approaches to model routing perform on MMLU-Pro, and what the spread reveals about the gap between a routing feature and a control layer for production AI.
StrategyAI Strategy Focused on Maximizing Returns on Your GenAI Investments
GenAI adoption is riddled with challenges: vendor lock-in, hallucinations, and spiraling costs. A control layer for production AI, with continuous evaluation, governance, and adaptive model selection, lets your team navigate them strategically.
ResearchLLM Routing in Practice: Surfing the LLM Waves with Intelligent Model Routing
New frontier LLMs arrive constantly. Should you migrate every time? Intelligent LLM routing makes it automatic — Divyam.AI's LLM router slashes a $100 inference bill to $42.40 with no quality loss on 60% of conversations.