Global Brands
Processing modes
Realtime when users are waiting.
Bulk when volume matters.
01
Realtime checks
Send one text when a user, review queue, or product workflow is waiting on a decision.
02
Bulk document scans
Submit many documents as one ordered job when you need a cheaper way to scan large sets.
Rate
$0.04 per 1,000 words20% cheaper
Limit
1,000 billable units
View API docs →
Why Pangram
Built for production
review systems
Detailed schema
Every completed analysis returns the same Pangram response fields for downstream scoring and review.
Designed for scale
Use Pangram as a product decision layer, a review queue signal, or a backfill tool for historical content.
Enterprise ready
Contact enterprise to Learn more about SOC 2 compliance, zero data retention options, and higher rate limits.
Response shape
Enough detail
for every use case
Quickstart
Start with a key and one predict() call
Create an account or log in, open the API tab, generate a key, and call Pangram from the Python SDK. The API key can be passed directly or read from PANGRAM_API_KEY.
Python SDK
Install the SDK, set PANGRAM_API_KEY, and call predict() with the text you want to analyze.
import os
from pangram import Pangram
client = Pangram(api_key=os.environ["PANGRAM_API_KEY"])
result = client.predict(
"The text to analyze with Pangram",
public_dashboard_link=False,
)
print(result["prediction_short"])
Credits and billing
Flexible billing options
Self-serve
Purchase credits
Buy $5-$2,000 in prepaid developer API credits from the purchase card above and start testing immediately.
Auto-refill
Keep your API balance topped up
Enable auto-refill during checkout to recharge your API balance when credits drop below the threshold you choose.
Bulk savings
20% cheaper for large jobs
Bulk jobs are charged at $0.04 per 1,000 words, giving teams a cheaper way to scan large document sets.
Enterprise
Security and higher limits
Contact enterprise to learn more about SOC 2 compliance, zero data retention options, and higher rate limits.
Examples
How teams use Pangram at scale
Use the API as a product decision layer, a review queue signal, or a backfill tool for historical content.
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