
Forecasting
Coming soonForecast future signal windows with optional language context.
Designed for operational planning, sensor monitoring, and anomaly follow-up.
Chronicle gives developers OpenAI-compatible endpoints for embeddings, retrieval, and signal intelligence across time-series and language data.
The API surface stays compact: send signal data and context, choose the model type that matches the workflow.

Encode time-series, text, and metadata into one retrieval space.
Search, cluster, classify, and retrieve signals with natural-language context.

Forecast future signal windows with optional language context.
Designed for operational planning, sensor monitoring, and anomaly follow-up.

Generate descriptions, incident summaries, and explanations from signal data.
Turn raw time-series windows into human-readable notes and reports.
Use the same client patterns teams already know. Change the base URL, choose a Chronicle model, and send text plus time-series inputs together.
from openai import OpenAI
client = OpenAI(
api_key="iai_...",
base_url="https://inertialai.com/api/v1",
)
response = client.embeddings.create(
model="chronicle-embed-alpha",
input={
"text": "pressure drop after thermal spike",
"time_series": [0.42, 1.87, 0.95, 2.31, 0.18],
},
)
embedding = response.data[0].embeddingUsage-based pricing for API models. No platform fees, no seat licenses, and no output charge for embeddings.
chronicle-embed-alphachronicle-embed-alphaEstimate monthly embedding usage by adjusting per-request context and request volume.
Based on chronicle-embed-alpha at $0.15 per 1M input tokens. Embedding output is not separately charged.
For proprietary data, high-volume workloads, and regulated environments.