Trusted by many, across their companies and within their products
LLUMO AI is powered by Eval360™
Eval360™ is a purpose-built SLM that evaluates and debugs agentic AI workflows at an atomic level to catch failures before they reach production.
LLUMO AI solutions
Why LLUMO AI Evals?
10X
Better visibility
Move beyond surface-level metrics. Evaluate inputs, outputs, reasoning, and workflows in one place.
80%
Faster issue detection
Instantly detect hallucinations, unsafe responses, & failures before they impact production.
4X
Stronger AI performance
Continuously measure, track, and improve system reliability using structured evaluation signals.
The one solution for Production LLM Applications
Seamlessly integrate and enhance LLMs performance, irrespective of language models or RAG setup.
Pre-Built Metrics Across the AI Pipeline
- Evaluate response quality and safety
- Detect relevance, toxicity, bias, and harmful intent
RAG-Based Metrics
Ensure responses are grounded in retrieved data by detecting hallucinations and measuring groundedness.
Agent & Workflow Metrics
Evaluate multi-step execution and reasoning by tracking tool usage, planning accuracy, and workflow consistency.
Structured Evaluation with Clear Signals
- Each run is scored across selected metrics
- Get clear signals on performance and reliability
Reasoning Behind Scores
Reasoning behind scores helps you understand why a response passed or failed, eliminating guesswork from debugging.
Multi-Metric Evaluation
Apply multiple metrics to the same run & analyze performance across different dimensions.
Custom Metrics for Your Use Case
- Go beyond generic evaluation with metrics tailored to your system
- Create custom metrics based on your domain requirements
Flexible Metric Definitions
Flexible metric definitions allow you to use structured inputs like query, context, and output, giving you control over how evaluation is performed.
Custom Scoring Framework
A custom scoring framework allows you to define score ranges and categories like Excellent, Good, or Poor, aligning evaluation with your benchmarks.
Domain-Specific Evaluation
Domain-specific evaluation allows you to build metrics tailored to industries like finance, legal, healthcare, support, and more.
Wall of love
Testimonials
Don't just take our word for it - see what actual users of our service have to say about their experience.
Nida
We used to spend hours digging through logs to trace where the agent went wrong. With the debugger, the flow diagram shows errors instantly, along with reasons and next steps.
Jazz Prado
Hallucinations in our customer support summaries were slipping through unnoticed. LLUMO’s debugger flagged them in real time, helping us prevent misinformation before it reached clients.
Shikhar Verma
Managing multi-agent workflows was messy, too many moving parts, too many blind spots. The debugger finally gave us clarity on what happened, why, and how to fix it.
Jordan M.
LLUMO felt like a flashlight in the dark. We cleared out hallucinations, boosted speeds, and can trust our pipelines again. It’s exactly what we needed for reliable AI.
Sarah K.
With LLUMO, we tested prompts, fixed hallucinations, and launched weeks early. It seriously leveled up our assistant’s reliability and gave us confidence in going live.
Nida
We used to spend hours digging through logs to trace where the agent went wrong. With the debugger, the flow diagram shows errors instantly, along with reasons and next steps.
Jazz Prado
Hallucinations in our customer support summaries were slipping through unnoticed. LLUMO’s debugger flagged them in real time, helping us prevent misinformation before it reached clients.
Shikhar Verma
Managing multi-agent workflows was messy, too many moving parts, too many blind spots. The debugger finally gave us clarity on what happened, why, and how to fix it.
Jordan M.
LLUMO felt like a flashlight in the dark. We cleared out hallucinations, boosted speeds, and can trust our pipelines again. It’s exactly what we needed for reliable AI.
Sarah K.
With LLUMO, we tested prompts, fixed hallucinations, and launched weeks early. It seriously leveled up our assistant’s reliability and gave us confidence in going live.
Nida
We used to spend hours digging through logs to trace where the agent went wrong. With the debugger, the flow diagram shows errors instantly, along with reasons and next steps.
Jazz Prado
Hallucinations in our customer support summaries were slipping through unnoticed. LLUMO’s debugger flagged them in real time, helping us prevent misinformation before it reached clients.
Shikhar Verma
Managing multi-agent workflows was messy, too many moving parts, too many blind spots. The debugger finally gave us clarity on what happened, why, and how to fix it.
Jordan M.
LLUMO felt like a flashlight in the dark. We cleared out hallucinations, boosted speeds, and can trust our pipelines again. It’s exactly what we needed for reliable AI.
Sarah K.
With LLUMO, we tested prompts, fixed hallucinations, and launched weeks early. It seriously leveled up our assistant’s reliability and gave us confidence in going live.
Mike L.
Integration was surprisingly quick, took less than 30 minutes. Now every agent run automatically and logs into the debugger, so we catch failures before they cascade.
Ryan
Before LLUMO, debugging meant replaying the entire workflow manually. With the SDK hooked in, we see real-time insights without changing how we build.
Sonia
Before LLUMO, we were stuck waiting on test cycles. Now, we can go from an idea to a working feature in a day. It’s been a huge boost for our AI product.
Amit Pathak
Our pipelines were growing complex fast. LLUMO brought clarity, reduced hallucinations, and sped up our inference, making our workflows feel rock solid.
Michael S.
I wasn’t sure if LLUMO would fit, but it clicked immediately. Debugging and evaluation became straightforward, and now it’s a key part of our stack.
Priya Rathore
Evaluating models used to be a guessing game. LLUMO’s EvalLM made it clear and structured, helping us improve models confidently without hidden surprises.
Mike L.
Integration was surprisingly quick, took less than 30 minutes. Now every agent run automatically and logs into the debugger, so we catch failures before they cascade.
Ryan
Before LLUMO, debugging meant replaying the entire workflow manually. With the SDK hooked in, we see real-time insights without changing how we build.
Sonia
Before LLUMO, we were stuck waiting on test cycles. Now, we can go from an idea to a working feature in a day. It’s been a huge boost for our AI product.
Amit Pathak
Our pipelines were growing complex fast. LLUMO brought clarity, reduced hallucinations, and sped up our inference, making our workflows feel rock solid.
Michael S.
I wasn’t sure if LLUMO would fit, but it clicked immediately. Debugging and evaluation became straightforward, and now it’s a key part of our stack.
Priya Rathore
Evaluating models used to be a guessing game. LLUMO’s EvalLM made it clear and structured, helping us improve models confidently without hidden surprises.
Mike L.
Integration was surprisingly quick, took less than 30 minutes. Now every agent run automatically and logs into the debugger, so we catch failures before they cascade.
Ryan
Before LLUMO, debugging meant replaying the entire workflow manually. With the SDK hooked in, we see real-time insights without changing how we build.
Sonia
Before LLUMO, we were stuck waiting on test cycles. Now, we can go from an idea to a working feature in a day. It’s been a huge boost for our AI product.
Amit Pathak
Our pipelines were growing complex fast. LLUMO brought clarity, reduced hallucinations, and sped up our inference, making our workflows feel rock solid.
Michael S.
I wasn’t sure if LLUMO would fit, but it clicked immediately. Debugging and evaluation became straightforward, and now it’s a key part of our stack.
Priya Rathore
Evaluating models used to be a guessing game. LLUMO’s EvalLM made it clear and structured, helping us improve models confidently without hidden surprises.
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FAQs
01 Can I try LLUMO AI for free?
02 Is LLUMO AI secure?
03 What models does LLUMO AI support?
04 Is LLUMO compatible with all LLMs and RAG frameworks?
05 Can I use LLUMO with custom-hosted LLMs?