aicoffeechat — Real-Time Conversational AI Observability

Capabilities

Everything your LLM tries to tell you

One unified view of token metrics, chat logs, tool calls, and generation traces — correlated automatically so you never miss a hallucination.

847K req/s

Real-Time Generation Streaming

Ingest millions of chat events per second from any provider. Zero-copy ingestion with sub-millisecond overhead to your LLM calls.

$ aicoffeechat ingest --stream production

✓ Connected to stream [production] · 847K events/s

✓ Context model loaded · avg TTFT: 42ms

⚡ Alert: Token generation spike in chat-gateway [3σ]

→ Root cause: recursive tool call detected

3 Anomalies

Semantic Anomaly AI

Adaptive ML evaluates chat intent and context. Detect multi-variate anomalies like topic drift or sudden sentiment drops with near-zero false positives.

hallucination · sales-bot

4.8σ

latency · rag-pipeline

3.2σ

cost/token · gpt-4

resolved

Semantic confidence 97.3%

Agentic Tracing

End-to-end trace visualization across agent steps. Pinpoint slow tool calls or vector DB latency with waterfall graphs.

user-msg

8ms

embed

45ms

pinecone

112ms

gpt-4-gen

840ms

Predictive Rate Limits

Get notified before OpenAI thresholds breach. Forecasting models predict rate limit hits 15–30 minutes ahead.

Native Model Integrations

Connect in minutes with OpenAI, Anthropic, LangChain, LlamaIndex, Pinecone, and every tool in your AI stack. No custom parsers needed.

OpenAI Anthropic LangChain Pinecone LlamaIndex Cohere HuggingFace Weaviate Milvus Vercel AI SDK

How it works

From raw prompt to
resolution in seconds

aicoffeechat collapses the gap between bad generation and prompt engineering. Our engine correlates, ranks, and routes every hallucination to the right dev automatically.

01

Ingest conversations

Send prompts, completions, and tool calls via our SDKs or OpenTelemetry. Minimal latency overhead.

OpenTelemetry native

02

Evaluate semantics

Our engine maps context relevance, sentiment, and toxicity — surfacing bad outputs instantly.

LLM-as-a-judge

03

Alert intelligently

AI-deduped alerts routed with full context — prompt history included. No noise.

Context aware

aicoffeechat · main-agent

LIVE

42ms

Avg TTFT

99.2%

Relevance Score

12

Open Issues

Token volume · 24h

Recent Insights

gpt-4o · latency normalized 2m ago

pinecone · index sync delayed 8m ago

sales-bot · off-topic generation detected 14m ago

Pricing

Transparent, usage-based pricing

No surprises. Pay for the tokens you trace. Scale from prototype to production on the same platform.

Monthly

Annual Save 20%

Starter

For indie devs and small agents getting started.

$0 / month

10M tokens traced / month

2 projects

7-day retention

Semantic anomaly detection

Trusted by AI engineers
at 2,400+ companies

"aicoffeechat cut our time resolving bad generations from hours to minutes. The semantic evaluator is genuinely magic — it spots context drops we'd never catch in logs."

Sarah L.

Staff AI Eng · FinTech Co

"We migrated our agent observability in a weekend. Same coverage, 60% less cost, and the UX is miles ahead. Tracing RAG pipelines is actually fun now."

Marcus R.

Platform Lead · Startup

"The predictive rate limit alerts gave us a 20-minute heads-up before our OpenAI tier capped out during a launch. We swapped to anthropic seamlessly."

Anika K.

VP Engineering · ScaleApp

"I've evaluated every LLM observability tool. aicoffeechat is the first one that feels like it was built by engineers who actually ship AI products."

James P.

Founding Engineer

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Find the signal through the noise — before it's too late