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 Debugger?
10X Faster
Debugging
Stop digging through scattered logs and traces. LLUMO visualizes every run step-by-step — from query to response — so you can instantly pinpoint where your AI workflow broke.
80% Fewer
Production issues
Hallucinations, tool failures, and hidden workflow errors often go unnoticed. LLUMO surfaces these signals early so teams can fix issues before they impact users.
4X Higher
Engineering productivity
With structured traces, automated evaluations, and clear failure attribution, teams spend less time investigating and more time improving AI reliability.
The one solution for Production LLM Applications
Seamlessly integrate and enhance LLMs performance, irrespective of language models or RAG setup.
Run Monitoring & Execution Health
- Success — The run is passed.
- Warning — The run is passed but something may go wrong in the future.
- Critical - The run is failed
Run Monitoring Dashboard
A centralized table displays all runs with key metadata including timestamps, run names, cost, token usage, and latency.
Advanced Run Filtering
Quickly isolate problematic runs by filtering based on input tokens, output tokens, cost, latency, and execution status.
Deep Trace Inspection
- Investigate the full context behind every AI response.
- View the entire payload including user query, retrieved context, generated output, and tools used.
Conversation & Context Tracking
Analyze message history, contextual data sources, and intermediate reasoning steps used by the model.
Token & Model Performance Metrics
Track token usage, response latency, inference cost, and the model responsible for generating the response.
Step-by-Step Workflow Debugging
- Understand how the AI system executed a task and where the failure occurred.
- Each run is mapped as a step-by-step workflow from query to final response.
Preset Evaluation Metrics
Built-in evaluation metrics analyze inputs and responses to detect toxicity, harmfulness, and other safety signals.
Custom Metric Creation
Create custom evaluation metrics to track domain-specific signals, or compliance beyond default metrics.
Overall Run Reliability Score
Each run receives an aggregated score that summarizes the overall reliability and quality of the execution.
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?