AI Observability Architecture • Full LLM Token & Trace Telemetry • Zero Per-Seat Fees

Hire a Ready-Made AI Observability Employee — or build a custom one in minutes

Stop running production LLM models in the dark without visibility into costs, latency, or hallucinations. Deploy an autonomous AI Observability Specialist that oversees 8 specialized sub-agents to trace multi-agent execution steps, monitor token budgets, prevent prompt injection, and audit accuracy 24/7.

Book a Live Demo Start 14-Day Free Trial No Card Needed View Live Console ↓
No credit card required Live within 15 minutes SOC 2 & GDPR compliant Native CRM & App integrations Zero per-seat user tax
8 Sub-Agents
LLM evaluation & monitoring squad
100%
Trace & execution visibility
-38%
Token spend optimization
Credit-Based
1,000 free credits • Plans from $20/mo
Live Interactive Console & Architecture

Primary AI Employee: AI Observability Director & LLMOps Lead

Experience how an autonomous primary AI Employee orchestrates 8 specialized sub-agents to vet data, enforce business rules, and trigger human approval gates in real time.

Live Orchestration Console

Active LLM Observability Desk • Production Model Telemetry Stream

Active Pipeline Mode Enterprise Stack Synced
LLM
Production Customer Support Agent • Model: Claude 3.5 Sonnet • Trace #TRC-89214 • Multi-Turn Support Conversation
Tokens: 1,420 • Latency: 640ms • Hallucination Score: 0.02 (Passing) • Cost: $0.004
Model Health: Optimal • 99%
Trace Inspector:
Evaluated 4 sub-agent tool call steps
Cost Optimizer:
Cached prompt prefix saving 620 tokens
Safety Guardrail:
Verified zero PII data leakage in output
AI Quality Gate: Hallucination score > 0.15 or cost spikes > $1.00 prompt LLMOps Lead sign-off.
Primary AI Employee: AI Observability Director & LLMOps Lead

Autonomous Model Evaluation & Guardrails Orchestrator

Maintains AI quality benchmarks, coordinates 8 observability sub-agents, enforces token budget constraints, prevents prompt injection, and audits hallucination rates across production models.

Autonomous Orchestrator Active v2.4
End-to-End Trace & Tool-Call Inspector
OpenTelemetry Traces
Hallucination & Groundedness Evaluator
RAG Verification
Token Cost & Budget Optimizer
30-50% Cost Reduction
Prompt Injection & Jailbreak Guard
Zero Jailbreaks
PII & Sensitive Data Redactor
PII Masking
Model Latency & Failover Router
TTFT Monitoring
Dataset Curator & Fine-Tuning Harvester
RLHF Data Collection
Observability Dashboard & Langfuse Sync
Langfuse & LangSmith
Rule Logic Preview Prompt injection attempts block instantly • Model latency >2,000ms triggers failover to lightweight model • Zero PII logging
Customize Rules
Flexible Deployment Spectrum

Three Ways to Put AI to Work in Your Team

Whether you want an instant out-of-the-box employee, want to adapt existing business rules, or need a fully bespoke custom AI employee, RhinoAgents gives you complete flexibility.

Option 1 • Instant Deployment

Hire a Ready-Made AI Observability Employee

Deploy an out-of-the-box AI Observability Specialist equipped with all 8 sub-agents. Integrates directly with Langfuse, Arize Phoenix, LangSmith, Helicone, and OpenTelemetry in 15 minutes.

  • All 8 specialized LLMOps & evaluation sub-agents enabled
  • Real-time semantic prompt caching and token cost optimization
  • Native connectors for Langfuse, LangSmith & OpenTelemetry
Hire Ready-Made Employee
Most Popular
Option 2 • No-Code Customization

Change Rules & Business Logic

Keep the ready-made employee architecture, but adapt the logic to your exact business operations. Adjust scoring thresholds, set custom knockout questions, alter tone, and define approval triggers.

  • Modify scoring rubrics & operational criteria
  • Set automated knockout filters for zero bad fits
  • Configure Slack human-in-the-loop review gates
Learn How to Edit Rules
Option 3 • Bespoke AI Employee

Create a Custom AI Employee

Build a custom AI observability employee tailored for regulated healthcare LLMs, automated red-teaming, or multi-modal vision model evaluations.

  • Custom role identity, persona & voice
  • Select which specialized sub-agents work under it
  • Connect to proprietary databases & webhooks
Build Custom AI Employee
Bespoke Creation Wizard

How to Create Your Custom AI Employee in 4 Steps

Need a purpose-built AI employee tailored to your organization? Use our intuitive step-by-step studio to define identity, channels, orchestrated sub-agents, and task execution logic.

Step 1 • Identity Configuration

Define Role Name, Avatar & Persona

Name your AI employee, upload or select a brand avatar, define its job title, and establish its core personality traits. Configure whether it communicates with a consultative corporate tone, an energetic sales cadence, or a friendly customer care voice.

Role Name & Title: e.g., "Enterprise AI Governance & Red-Team Lead"
Persona Definition: Set brand voice guidelines, communication policies, and greeting formats.
Avatar & Bio: Establish internal and customer-facing profile visuals.
Step 1 Identity Studio
Autonomous Multi-Agent Workflow

How Sub-Agents Collaborate Under the AI Employee

Sub-agents do not operate as disconnected single-purpose bots. They operate as a synchronized squad orchestrated by the primary AI Employee, exchanging context and data in real time.

1

Signal & Intake

Inquiry or record is ingested from web chat, email, form submission, or webhook. Primary AI Employee verifies context and dispatches it to the Intake sub-agent.

Trigger: Signal Received
2

Enrichment & Vetting

Data is parsed against your custom rubrics. Sub-agents verify external databases, enrich missing parameters, and calculate objective qualification scores.

Logic: Custom Rubrics
3

Gate Evaluation

Scores meeting your auto-advance threshold proceed immediately. Borderline cases generate an executive summary card to a designated Slack channel for human 1-click review.

Security: Human-in-the-Loop
4

Action & 360° Sync

Sub-agents book calendar invites, trigger confirmation notifications, and write full audit logs into your CRM, ERP, and database systems automatically.

Output: Closed-Loop Execution
Modular Sub-Agent Squad

8 Ready-Made Sub-Agents at Your Service

Each sub-agent is an autonomous specialist. Use them together under the Primary AI Employee or configure individual rules, knockouts, and triggers for each.

Sub-Agent 01

End-to-End Trace & Tool-Call Inspector

Traces complex multi-step reasoning, tool invocations, and subagent handoffs to identify execution bottlenecks and loop failures.

Trigger: Model generation execution
Output: Complete execution trace graph
OpenTelemetry Traces Subagent Call Graphs
Sub-Agent 02

Hallucination & Groundedness Evaluator

Evaluates LLM responses against source knowledge documents, calculating factual consistency scores and blocking ungrounded claims.

Trigger: Generated response output
Output: Groundedness & hallucination score
RAG Verification Factual Consistency
Sub-Agent 03

Token Cost & Budget Optimizer

Tracks token consumption across models (OpenAI, Anthropic, Gemini), applying semantic prompt caching to cut API bills by 30-50%.

Trigger: API request dispatched
Output: Token cost analytics & cache hit
30-50% Cost Reduction Semantic Prompt Caching
Sub-Agent 04

Prompt Injection & Jailbreak Guard

Detects adversarial prompt injections, system prompt extraction attempts, and jailbreaks in real time, neutralizing malicious inputs.

Trigger: User prompt received
Output: Adversarial threat evaluation
Zero Jailbreaks Prompt Injection Defense
Sub-Agent 05

PII & Sensitive Data Redactor

Identifies and masks Social Security numbers, credit card data, API keys, and passwords before prompts are sent to external LLM providers.

Trigger: Prompt ingestion stage
Output: Anonymized prompt & tokenized PII
PII Masking GDPR / HIPAA Safe
Sub-Agent 06

Model Latency & Failover Router

Monitors TTFT (Time to First Token) and total latency, automatically failing over to backup models or secondary cloud regions when APIs stall.

Trigger: Latency exceeds 1,500ms threshold
Output: Dynamic failover routing
TTFT Monitoring Multi-Provider Failover
Sub-Agent 07

Dataset Curator & Fine-Tuning Harvester

Collects high-quality user interactions and positive feedback, formatting clean JSONL datasets for continuous model fine-tuning.

Trigger: Positive interaction logged
Output: Curated fine-tuning dataset JSONL
RLHF Data Collection Curated Training Sets
Sub-Agent 08

Observability Dashboard & Langfuse Sync

Aggregates accuracy, cost, and latency metrics directly into Langfuse, LangSmith, Arize Phoenix, or Datadog LLM dashboards.

Trigger: Metric aggregation cycle
Output: Synchronized LLMOps telemetry
Langfuse & LangSmith Live Telemetry Dashboards
No-Code Rule Customization

How to Change Rules & Customize Logic

You never have to accept a rigid black-box AI. Every scoring weight, knockout condition, tone guideline, and approval gate can be altered in seconds using visual toggles or natural language.

1. Adjust Scoring Weights

Use visual percentage sliders to weight qualification rubrics (e.g. 40% Fit Criteria, 30% Budget/Timeline, 20% Tech Stack, 10% Profile Quality).

Core Fit:40%
Authority / Budget:30%

2. Set Mandatory Knockout Criteria

Add non-negotiable prerequisite rules. If an inquiry fails any knockout criteria, it is politely handled with an automated response without wasting your team's time.

Minimum budget threshold met
Corporate business email domain
Operating in serviceable geographic territory

3. Set Human Approval Thresholds

Define exact score brackets that trigger instant execution versus those requiring human team sign-off via Slack or email.

• Score ≥ 85: Auto-execute
• Score 70-84: Slack Team 1-Click Gate
• Score < 70: Polite automated routing
Natural Language Rule Modification

Or Simply Edit Rules in Plain English

Zero Code Required
// Type plain English prompt to change rules:
"Prompt injection attempts block instantly • Model latency >2,000ms triggers failover to lightweight model • Zero PII logging"
RhinoAgents Logic Engine Compiles:
  • • Evaluates criteria ≥ 200 units → Rule Tag: TIER_1_VIP
  • • Trigger action → CALENDAR_SYNC_SENIOR_PANEL
  • • Webhook → SLACK_DISPATCH(#sales-leads)
Applied instantly across all 8 sub-agents Live Status: Active
Ideal Fit

Built for Modern Teams Across Every Scale

From agile high-velocity startups to established enterprise organizations, deploy an autonomous AI Observability Employee tailored to your operational velocity.

Cloud-Native Teams

Cloud Engineering & DevOps Teams

Autonomous telemetry inspection, root-cause correlation, and auto-remediation runbooks across microservices.

Continuous Telemetry
Enterprise SREs

Site Reliability Organizations

Cut alert noise by 70%, correlate cross-service traces, and trigger instant PagerDuty escalations for genuine P0s.

70% Less Noise
SecOps & InfoSec

Security Operations Centers (SOC)

Block prompt injection attacks, neutralize credential leak attempts, and maintain continuous GDPR logs.

Active Threat Defense
Managed Service Providers

MSPs & IT Infrastructure Hosts

Provide 24/7 autonomous client monitoring, ticket classification, and automated node failovers.

24/7 SLA Guarantee
Proven Operational ROI

Measurable Advantages for Modern Organizations

Replacing administrative manual labor with an autonomous AI Observability Employee delivers direct returns on execution speed, operational accuracy, and staffing overhead.

80% Faster Incident MTTD

Detect infrastructure anomalies, latency spikes, and security drifts in seconds across telemetry.

70% Less Alert Fatigue

Intelligent deduplication filters noise and only alerts your on-call engineers for genuine P0/P1s.

Instant Automated Runbooks

Executes pre-approved remediation scripts, spins down degraded nodes, and logs recovery steps.

Zero Prompt Injection Risks

Security sub-agents inspect inputs before LLMs process them, protecting proprietary company data.

8-Specialist SRE Squad

Telemetry monitoring, anomaly detection, root-cause triage, and post-mortem creation working as one.

Native DevOps Stack Sync

Full bidirectional connectivity with Langfuse, Datadog, PagerDuty, Slack, Jira, and GitHub.

Ecosystem Connectors

Native Integrations with Your Existing Stack

Connect your CRM, messaging channels, databases, and enterprise tools in seconds. The AI employee synchronizes updates automatically without changing your team's workflow.

Langfuse Datadog Prometheus Grafana OpenTelemetry AWS CloudWatch PagerDuty Jira Software GitHub Snyk Slack 400+ More Integrations →
Frequently Asked Questions

Got Questions? We Have Answers.

Everything you need to know about hiring, customizing, and scaling autonomous AI employees.

An AI Observability Employee is an autonomous digital monitoring specialist that tracks your production AI models and agents. It inspects execution traces, optimizes token costs, prevents prompt injections, and audits output accuracy in real time.

RhinoAgents operates on a transparent credit-based model with zero per-seat human fees. You start with 1,000 free execution credits on our Free Trial ($0). Monthly plans start at $20/month (Starter: 10,000 credits/mo), $49/month (Pro: 50,000 credits/mo), and $99/month (Business: 150,000 credits/mo). Credits are consumed based on task complexity (such as research, data processing, workflow orchestration, communication, or CRM/ERP syncing). Unlimited human team members can access and collaborate with the AI employee without paying user seat penalties.

We support native integrations with Langfuse, LangSmith, Arize Phoenix, Helicone, Weights & Biases, OpenTelemetry, and Datadog LLM Observability.

Yes. Our Security Guardrail sub-agent inspects user inputs before they reach the model, neutralizing prompt injections, jailbreaks, and attempts to leak internal system instructions.

RhinoAgents operates on a transparent credit-based model with zero per-seat human fees. You start with 1,000 free execution credits on our Free Trial ($0). Monthly plans start at $20/month (Starter: 10,000 credits/mo), $49/month (Pro: 50,000 credits/mo), and $99/month (Business: 150,000 credits/mo). Credits are consumed based on task complexity (such as research, data processing, workflow orchestration, communication, or CRM/ERP syncing). Unlimited human team members can access and collaborate with the AI employee without paying user seat penalties.

RhinoAgents pays for 100% of the underlying AI model costs (LLM tokens for GPT-4o, Claude 3.5 Sonnet, Gemini, etc.) and cloud computing infrastructure—all covered directly by your monthly credit allotment. You never need to supply your own OpenAI or Anthropic API keys. The customer is only responsible for their own external third-party software subscriptions and tool accounts (such as your existing CRM, ATS, Twilio, WhatsApp Business API, ERP, or cloud accounts). RhinoAgents connects seamlessly via 1-click native integrations with zero markup.

Get Started in Minutes

Put Your Autonomous AI Observability Employee to Work Today

Deploy in 15 minutes. Connect your CRM, email, and tools with 1-click connectors. Experience the power of an orchestrated AI team without adding headcount.

Book a Live Demo Start 14-Day Free Trial
No credit card required 15-Minute Quick Setup SOC 2 & GDPR Compliant No Per-Seat Human Fees