Neotask automates your LLM observability pipeline through Arize Phoenix - monitoring traces, managing prompts, and running experiments so your AI systems stay reliable.
LLM pipeline health gets monitored automatically - your agent inspects traces, flags failing spans, and surfaces annotation issues before they reach production
Prompt engineering becomes a managed workflow - version control, tagging, and A/B testing of prompts happen through conversation instead of manual iteration
Evaluation datasets grow from real production data - your agent captures traces, adds them as test examples, and runs regression experiments automatically
What You Can Do
Your AI agent turns Arize Phoenix into a fully automated LLM observability operation. It monitors your AI pipelines, manages prompt versions, and runs experiments - keeping your models reliable without constant manual oversight.
Pipeline Monitoring
Your agent continuously inspects traces and spans across projects. It identifies error patterns, reviews span annotations, and surfaces sessions where quality degraded. Schedule regular health checks and get alerted before issues reach users.
Prompt Lifecycle Management
Manage prompts as versioned, tagged assets. Your agent creates new versions, tags releases as production or staging, and tracks iteration history. When you need to roll back, it knows every version that ever existed.
Automated Experimentation
Build evaluation datasets from real production traces. Your agent adds examples from interesting spans, runs experiments against datasets, and compares results across prompt versions. Quantify improvements before deploying them.
Area
What Your Agent Handles
Prompts
Version management, tagging, upserts, iteration tracking
Traces & Spans
Inspection, annotation review, error detection
Datasets
Example management, experiment execution, regression testing
Projects
Multi-project monitoring, session tracking, health checks
Every action runs autonomously or requires your approval - you decide.
Try Asking
"Check all traces from the last hour and flag any with error spans"
"Tag the latest version of our 'customer-support' prompt as 'production'"
"Add the 10 most recent failed traces as examples to our regression test dataset"
"Run an experiment comparing prompt v4 against v5 on the 'classification' dataset"
"What annotations exist for spans in the 'search-pipeline' project?"
"Show me all sessions from today with more than 3 turns"
"List every prompt version we've deployed to production in the last month"
"Create a new prompt called 'invoice-extractor' from this template"
Pro Tips
Schedule hourly trace checks during high-traffic periods - your agent catches regressions before they compound
Use approval gates for prompt version tagging - review changes before marking anything as production
Multi-agent teams excel here: one agent monitors traces, another manages prompts, a third runs experiments
Build regression datasets from real failures - they catch edge cases synthetic data misses
Session-level analysis reveals multi-turn conversation issues that single-trace inspection misses
Combine Phoenix with your alerting integration to get notified the moment trace quality drops
Multiple workspaces and capacity for larger teams.
Works Well With
BigQuery - Connect Arize Phoenix with BigQuery to sync ML model metrics, traces, and observability data directly into your data war...
Google Slides - Connect Arize Phoenix to Google Slides to automate ML observability reporting and share AI model monitoring insights as ...
Microsoft 365 - Connect Arize Phoenix ML observability with Microsoft 365. Send AI model monitoring reports to Teams, automate alerts, a...
More AI & ML Integrations
Label Studio - Manage data labeling projects and annotations through conversation - Neotask uses AI agents to operate your Label Studio annotation infrastructure.
Anthropic - Call Claude models, manage prompts, and monitor usage - Neotask orchestrates your Anthropic API.
Scholar Gateway - Neotask connects your research workflows to Wiley's Scholar Gateway - running semantic search across peer-reviewed scientific literature to ground your work in authoritative sources.
Stability AI - Generate, edit, and transform images with Stable Diffusion - Neotask runs your Stability AI workflows.
Cohere - Generate text, rerank results, and build enterprise search - Neotask puts Cohere's NLP suite to work.
Replicate - Run ML models in the cloud with a single instruction - Neotask orchestrates your Replicate predictions.