This dataset requires a paid license. Please purchase access at the link below and provide your Hugging Face username. Once purchased, submit an access request on this page. Access is granted manually.

AI Receptionist Pricing and Call Automation Dataset

A source-backed market-intelligence dataset for comparing AI receptionists, voice agents, and phone automation platforms across pricing surfaces, appointment workflows, CRM coverage, compliance claims, and deployment style.

Each row represents one observed signal from an official product page, official pricing page, official help center page, or official documentation page for an AI receptionist or voice-agent platform. The dataset is built for procurement research, competitive analysis, partner due diligence, pricing comparisons, call-automation market mapping, and shortlist creation. It is not a ranking of vendor quality and does not guarantee business outcomes.

Access Requirements (Paid Dataset)

This dataset is behind manual gated access.

To obtain access:

Purchase the dataset here:
https://thearticulated.gumroad.com/l/advwdf?utm_source=hf_paid_readme&utm_medium=referral&utm_campaign=ai-receptionist-pricing-and-call-automation-signals
Provide your Hugging Face username at checkout.
Return to this Hugging Face page and click:
"Request Access"
Your access will be approved within 1-12 hours.

Once approved, you can use the Python snippet at the bottom of this README to load the dataset.

Dataset Structure

Total rows: 287

Total columns: 37

Splits

data: 287 rows

Data Files

data: data/data.parquet

Data Dictionary

The table below describes the columns included in this dataset.

column	pandas_dtype	dataset_type	description
record_id	object	string	Text column. Stable unique identifier for the observed source-backed signal row.
vendor_id	object	string	Text column. Machine-friendly slug for the platform vendor or product.
vendor_name	object	string	Text column. Display name of the AI receptionist or voice-agent platform.
vendor_segment	object	string	Text column. High-level market segment such as developer-platform, smb-platform, enterprise-platform, restaurant-platform, or ucaas-platform.
target_buyer	object	string	Text column. Primary buyer persona or procurement workflow the platform appears to target.
official_website_url	object	string	Text column. Primary official website URL for the vendor or product.
source_url	object	string	Text column. Exact official source URL used for the row-level signal.
source_domain	object	string	Text column. Domain extracted from the source URL.
source_type	object	string	Text column. Type of source page, such as official pricing page, official product page, or official help center page.
source_title	object	string	Text column. HTML title of the official source page when available.
signal_type	object	string	Text column. Broad row family, such as page_summary, pricing_signal, or capability_signal.
signal_category	object	string	Text column. Specific signal grouping, such as pricing, inbound_calls, appointment_booking, crm_integration, or compliance.
signal_name	object	string	Text column. Normalized machine-friendly signal name.
signal_value_text	object	long text	Free-text column containing longer text values. Human-readable row value or claim text normalized from the official page.
normalized_signal_value	object	string	Text column. Compact normalized value label used for grouping similar claims.
price_amount_usd	float64	float	Decimal numeric column. Parsed numeric USD price when the source sentence contained a price-like value and it was safe to normalize.
price_metric	object	string	Text column. Best-effort metric attached to the observed price, such as per_month, per_minute, per_year, credit_based, or general_price_signal.
pricing_transparency	object	string	Text column. Best-effort yes, no, or partial flag describing whether the source exposes self-serve pricing on the page.
pricing_model_summary	object	string	Text column. Concise summary of the page pricing style, such as transparent tiered pricing, usage-based pricing, or contact-sales pricing.
inbound_calls_support	object	string	Text column. Best-effort yes, no, or unknown flag for inbound call handling support.
outbound_calls_support	object	string	Text column. Best-effort yes, no, or unknown flag for outbound calling or follow-up support.
appointment_booking_support	object	string	Text column. Best-effort yes, no, or unknown flag for appointment booking or scheduling workflows.
sms_support	object	string	Text column. Best-effort yes, no, or unknown flag for text or SMS support claims.
crm_integration_support	object	string	Text column. Best-effort yes, no, or unknown flag for CRM or CRM-adjacent integration claims.
human_handoff_support	object	string	Text column. Best-effort yes, no, or unknown flag for human transfer or escalation claims.
api_or_sdk_support	object	string	Text column. Best-effort yes, no, or unknown flag for API, SDK, or developer-platform claims.
no_code_builder_support	object	string	Text column. Best-effort yes, no, or unknown flag for no-code setup or builder claims.
multilingual_support	object	string	Text column. Best-effort yes, no, or unknown flag for multilingual or multi-language support claims.
hipaa_claim	object	string	Text column. Best-effort yes, no, or unknown flag for HIPAA-related claims on the source page.
gdpr_claim	object	string	Text column. Best-effort yes, no, or unknown flag for GDPR-related claims on the source page.
industry_focus_tags	object	string	Text column. Pipe-delimited industry or workflow tags inferred from official page language.
confidence_score	int32	integer	Whole-number numeric column. Directional 0-100 confidence score based on how directly the source supports the normalized row.
confidence_level	object	string	Text column. Text label derived from the confidence score.
notes	object	string	Text column. Interpretation notes or caveats for the row.
source_excerpt	object	long text	Free-text column containing longer text values. Short supporting excerpt from the official page used to build the signal row.
observed_date	datetime64[ns, UTC]	datetime	Date or timestamp column. UTC date when the source page was observed during collection.
last_collected_at	datetime64[ns, UTC]	datetime	Date or timestamp column. UTC timestamp when the extraction run collected the row.

Intended Use

This dataset is intended for research, experimentation, analysis, and model prototyping.

Loading the Dataset


import os
from datasets import load_dataset

HUGGINGFACE_API_KEY_KARMANE = os.environ.get("HUGGINGFACE_API_KEY_KARMANE")

dataset = load_dataset(
    "Karmane/ai-receptionist-pricing-and-call-automation-signals",
    token=HUGGINGFACE_API_KEY_KARMANE,
)

print(dataset)
print(dataset[list(dataset.keys())[0]][0])

# getting the DataFrame itself
# df = dataset[list(dataset.keys())[0]].to_pandas()

Karmane. (2025). AI Receptionist Pricing and Call Automation Dataset. Hugging Face. https://huggingface.co/datasets/Karmane/ai-receptionist-pricing-and-call-automation-signals

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