Simple pricing for modern teams

Start for free. Upgrade when you need to process more volume.

Developer

Perfect for evaluating the API and building proof of concepts.

$0/mo
Get Started Free
Most Popular

Growth

For ops teams scaling their inbound lead workflows.

$49/mo
Start 14-Day Trial

Scale

For high-volume automation and CRM syncing.

$199/mo
Start 14-Day Trial

Enterprise

Custom SLA, dedicated support, and bespoke models.

Custom
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Compare Features

DeveloperGrowthScaleEnterprise
Records extracted / monthUp to 100Up to 3,000Up to 1MUp to 10M
Multiple pipelinesUnlimitedUnlimitedUnlimitedUnlimited
Extracted fieldsUnlimitedUnlimitedUnlimitedUnlimited
AI parsing engine
Template parsing engine
Routing rules
Integrations & Export
CSV / Excel export
Google Sheets sync
Webhooks
REST API access
Salesforce / HubSpot sync
Support & Security
Data retention7 days30 days1 yearCustom
Support levelCommunityEmailPriorityDedicated Slack
Role-based access
Custom SLA

Common Questions

Everything you need to know about the platform.

Absolutely. Because AerisL allows you to create relational datasets and custom workflows, many teams use it as a highly customizable, lightweight CRM that automatically parses emails and populates lead data without any manual entry.

AerisL uses large language models (like Gemini) to understand the context of documents, rather than relying on strict visual templates. This means whether a prospect sends a custom inquiry or a vendor changes their invoice format, the AI still correctly identifies the necessary data points.

Yes. AerisL has a visual workflow builder that allows you to configure webhooks, API requests, and conditional logic to push extracted datasets directly into Salesforce, SAP, NetSuite, HubSpot, or custom databases.

We offer Enterprise-grade Role-Based Access Control (RBAC). You can create Organizations, Workspaces, and Teams. Permissions can be set so specific teams (like Sales or Finance) only see data relevant to them, and sensitive PII can be automatically redacted.

Every extraction receives a confidence score. You can set workflow rules to automatically route low-confidence extractions (e.g., under 95%) to a human-in-the-loop queue for manual review by your team before the data hits your database.