Fix AI Failures Before They Impact Performance

LLUMO's Debugger pinpoint failures, provides automated root cause analysis, apply fixes, and make AI workflows reliable.

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Trusted by many, across their companies and within their products

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LLUMO AI solutions

Why LLUMO AI Debugger?

10X

Faster debugging

Skip sifting through messy logs. see exactly where your AI agents failed — from input to output — and resolve errors in real time.

80%

Reduced issues

Silent bugs and hallucinations can wreck workflows. LLUMO surfaces them instantly, so you can correct mistakes before they impact users.

4X

Productivity

Ensure enterprise-grade reliability, robust guardrails, and continuous behavior monitoring — delivering stable, explainable AI at scale.

Available Integrations

Seamlessly integrate and enhance LLMs performance, irrespective of language models or RAG setup.

nvidia
openai
m
mistralai
meta
langchain
lamaindex
hugging-face
Haystack
Cohere
Bard
Anthropic
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llumo-llm-connections

Precision debugging & investigation

  • View exactly what happened inside LLM workflows, from query, tool planning to execution outcomes.
  • Automated root cause analysis & impact metrics helps you prioritize fixes based on prevalence & business impact.
Evaluate | Optimize | Automate - in one click! illusration

Session-level precision

View performance and outcomes per session-session Name, Total Runs, Status, Latency, Score, Timestamp-so you can trace issue origins.

The Ultimate LLM Testing Playground

Clarity, not confusion 

From flow visualization to detailed traces and logs, the Debugger turns obscure errors into actionable insights.

Same output at a lower cost illustration

Intelligent issue detection

  • Identify silent failures across single and multi-agent workflows - and get structured, actionable next steps.
  • You don't just detect errors - you understand them deeply, fix them strategically and measure improvement over time.
Save Up to 80% on LLM Costs illustration

Affected runs (trace logs)

Concrete run examples (e.g., run-003 -> invoked CREATE_CRM_RECORD) highlight where things went wrong.

Same output at a lower cost illustration

Impact metrics & timeline

See how widespread the issue is and when it occurred-helping you prioritize and track resolution.

Compression, Routing & Caching illustration

Optimized reliability & scale

  • Fix misclassifications, workflow blindspots, and suppressed warnings systematically.
  • Refine outputs using structured contextual feedback to reduce hallucinations and inaccuracies.
360° LLM Performance Visibility illustration

Agent reliability & audit

Trace agent decisions, planning & tool usage step-by-step for transparency. Enforce guardrails and log every action for full explainability in production.

Easy integration & scalability

Connect via SDK to existing agents or AI Pipelines without coding overhead. Scale multi-agent orchestrations while maintaining auditability & reliability.

Hallucination & error reduction

The 360-view-trace, explanation, tech detail-lets you identify failure points swiftly, measure performance, and understand system behavior deeply.

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

Nida

Co-founder & CEO, Nife.io

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

Jazz Prado

Project Manager, Beam.gg

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

Shikhar Verma

CTO, Speaktrack.ai

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.

Jordan M.

VP, CortexCloud

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.

Sarah K.

Lead NLP Scientist, AetherIQ

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

Nida

Co-founder & CEO, Nife.io

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

Jazz Prado

Project Manager, Beam.gg

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

Shikhar Verma

CTO, Speaktrack.ai

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.

Jordan M.

VP, CortexCloud

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.

Sarah K.

Lead NLP Scientist, AetherIQ

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

Nida

Co-founder & CEO, Nife.io

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

Jazz Prado

Project Manager, Beam.gg

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

Shikhar Verma

CTO, Speaktrack.ai

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.

Jordan M.

VP, CortexCloud

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.

Sarah K.

Lead NLP Scientist, AetherIQ

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.

Mike L.

Senior LLM Engineer, OptiMind

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

Ryan

CTO at ClearView AI

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

Sonia

Product Lead at AI Novus

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

Amit Pathak

Head of Operations at VerityAI

Our pipelines were growing complex fast. LLUMO brought clarity, reduced hallucinations, and sped up our inference, making our workflows feel rock solid.

Michael S.

Michael S.

AI Lead at MindWave

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

Priya Rathore

AI engineer at NexGen AI

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.

Mike L.

Senior LLM Engineer, OptiMind

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

Ryan

CTO at ClearView AI

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

Sonia

Product Lead at AI Novus

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

Amit Pathak

Head of Operations at VerityAI

Our pipelines were growing complex fast. LLUMO brought clarity, reduced hallucinations, and sped up our inference, making our workflows feel rock solid.

Michael S.

Michael S.

AI Lead at MindWave

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

Priya Rathore

AI engineer at NexGen AI

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.

Mike L.

Senior LLM Engineer, OptiMind

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

Ryan

CTO at ClearView AI

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

Sonia

Product Lead at AI Novus

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

Amit Pathak

Head of Operations at VerityAI

Our pipelines were growing complex fast. LLUMO brought clarity, reduced hallucinations, and sped up our inference, making our workflows feel rock solid.

Michael S.

Michael S.

AI Lead at MindWave

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

Priya Rathore

AI engineer at NexGen AI

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?

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