Nida
Co-founder & CEO, Nife.io
We've got a plan for you
Starter
Getting started with Logging + Observability
Free*
What's included:
- Users: 1
- Logs: 10,000 runs / month
- Eval360™ SLM: 0 runs / month
- Structured Logging
- Debug Lens
- Custom Evals
- Observe Dashboard
- Best for: MVPs • POCs • early prompt iteration
Observability, Tracing & Analytics
CLLM application & agent tracing
Agent graphs & execution flows
Session tracking (chats / threads)
User-level tracking
Token usage & cost tracking
Access to historical data
SLA monitoring & reliability metrics
Prompt, Experimentation & Evaluation
Automated Logging
Debug Lens
Advanced Debugger
Actionable Insights
Simulation
Prompt experiments (A/B testing)
Experiments via UI
Experiments via UI
Integration via MCPs
Evaluation scores (custom metrics)
Eval360™ SLM
Human annotation
Human annotation queues
User feedback tracking
External evaluation pipelines
Integrations, SDKs & Extensibility
Native framework integrations
LangChain
LlamaIndex
Guardrails
SDKs
Python
JavaScript
OpenTelemetry support (Java, Go, custom)
Webhooks
Slack integration
Custom model webhooks
Knowledge bases & document readers
Vertex AI support
LLUMO API access
Security, Access & Enterprise Support
Security & Compliance
Data region selection
Data masking
Data retention management
AES-256 encryption
TLS 1.3 / SSL
MFA
SOC 2 Type II
GDPR data processing agreement (DPA)
SSO via Google
Enterprise SSO (Okta, Azure AD / Entra ID)
SSO enforcement
Organization-level RBAC
Project-level RBAC
Dedicated company domain
Support & Services
Community Slack
Private Slack channel
Dedicated support engineer
Dedicated account manager
Onboarding & architectural guidance
Live demos & e-meet support
Priority support with defined support SLA
Multiple projects
Enterprise-wide admin panel
On-premise hosting
Data exports
Batch exports via UI
Pro
For growing teams & production workloads
$49*/month
What's included:
- Everything in Starter, plus
- Users: Unlimited
- Logs: 25,000 runs / month
- Eval360™ SLM: 5,000 runs / month
- Note: Runs beyond 5,000 are billed at $6 per 1,000 runs for Eval360™ SLM
- Eval360™ SLM
- Real-time Reliability control
- Debugger Insights
- Simulation
- Best for: Agentic Pipelines • RAG • LLM Apps
Observability, Tracing & Analytics
CLLM application & agent tracing
Agent graphs & execution flows
Session tracking (chats / threads)
User-level tracking
Token usage & cost tracking
Access to historical data
SLA monitoring & reliability metrics
Prompt, Experimentation & Evaluation
Automated Logging
Debug Lens
Advanced Debugger
Actionable Insights
Simulation
Prompt experiments (A/B testing)
Experiments via UI
Experiments via UI
Integration via MCPs
Evaluation scores (custom metrics)
Eval360™ SLM
Human annotation
Human annotation queues
User feedback tracking
External evaluation pipelines
Integrations, SDKs & Extensibility
Native framework integrations
LangChain
LlamaIndex
Guardrails
SDKs
Python
JavaScript
OpenTelemetry support (Java, Go, custom)
Webhooks
Slack integration
Custom model webhooks
Knowledge bases & document readers
Vertex AI support
LLUMO API access
Security, Access & Enterprise Support
Security & Compliance
Data region selection
Data masking
Data retention management
AES-256 encryption
TLS 1.3 / SSL
MFA
SOC 2 Type II
GDPR data processing agreement (DPA)
SSO via Google
Enterprise SSO (Okta, Azure AD / Entra ID)
SSO enforcement
Organization-level RBAC
Project-level RBAC
Dedicated company domain
Support & Services
Community Slack
Private Slack channel
Dedicated support engineer
Dedicated account manager
Onboarding & architectural guidance
Live demos & e-meet support
Priority support with defined support SLA
Multiple projects
Enterprise-wide admin panel
On-premise hosting
Data exports
Batch exports via UI
Enterprise
For high-scale production systems & regulated orgs
Let's talk
What's included:
- Everything in Pro, plus
- Users: Unlimited
- Logs: Unlimited
- Eval360™ SLM: Unlimited
- Role-based access control (RBAC)
- Single Sign-On (SSO)
- On-premise Eval 360 SLM
- Dedicated account manager
- Security + compliance
- SLA + Priority support
- Best for: Enterprise-scale AI apps • mission-critical deployments
Observability, Tracing & Analytics
CLLM application & agent tracing
Agent graphs & execution flows
Session tracking (chats / threads)
User-level tracking
Token usage & cost tracking
Access to historical data
SLA monitoring & reliability metrics
Prompt, Experimentation & Evaluation
Automated Logging
Debug Lens
Advanced Debugger
Actionable Insights
Simulation
Prompt experiments (A/B testing)
Experiments via UI
Experiments via UI
Integration via MCPs
Evaluation scores (custom metrics)
Eval360™ SLM
Human annotation
Human annotation queues
User feedback tracking
External evaluation pipelines
Integrations, SDKs & Extensibility
Native framework integrations
LangChain
LlamaIndex
Guardrails
SDKs
Python
JavaScript
OpenTelemetry support (Java, Go, custom)
Webhooks
Slack integration
Custom model webhooks
Knowledge bases & document readers
Vertex AI support
LLUMO API access
Security, Access & Enterprise Support
Security & Compliance
Data region selection
Data masking
Data retention management
AES-256 encryption
TLS 1.3 / SSL
MFA
SOC 2 Type II
GDPR data processing agreement (DPA)
SSO via Google
Enterprise SSO (Okta, Azure AD / Entra ID)
SSO enforcement
Organization-level RBAC
Project-level RBAC
Dedicated company domain
Support & Services
Community Slack
Private Slack channel
Dedicated support engineer
Dedicated account manager
Onboarding & architectural guidance
Live demos & e-meet support
Priority support with defined support SLA
Multiple projects
Enterprise-wide admin panel
On-premise hosting
Data exports
Batch exports via UI
Observability, Tracing & Analytics
CLLM application & agent tracing
Agent graphs & execution flows
Session tracking (chats / threads)
User-level tracking
Token usage & cost tracking
Access to historical data
SLA monitoring & reliability metrics
Prompt, Experimentation & Evaluation
Automated Logging
Debug Lens
Advanced Debugger
Actionable Insights
Simulation
Prompt experiments (A/B testing)
Experiments via UI
Experiments via UI
Integration via MCPs
Evaluation scores (custom metrics)
Eval360™ SLM
Human annotation
Human annotation queues
User feedback tracking
External evaluation pipelines
Integrations, SDKs & Extensibility
Native framework integrations
LangChain
LlamaIndex
Guardrails
SDKs
Python
JavaScript
OpenTelemetry support (Java, Go, custom)
Webhooks
Slack integration
Custom model webhooks
Knowledge bases & document readers
Vertex AI support
LLUMO API access
Security, Access & Enterprise Support
Security & Compliance
Data region selection
Data masking
Data retention management
AES-256 encryption
TLS 1.3 / SSL
MFA
SOC 2 Type II
GDPR data processing agreement (DPA)
SSO via Google
Enterprise SSO (Okta, Azure AD / Entra ID)
SSO enforcement
Organization-level RBAC
Project-level RBAC
Dedicated company domain
Support & Services
Community Slack
Private Slack channel
Dedicated support engineer
Dedicated account manager
Onboarding & architectural guidance
Live demos & e-meet support
Priority support with defined support SLA
Multiple projects
Enterprise-wide admin panel
On-premise hosting
Data exports
Batch exports via UI
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.
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?