Airgap vs Mostly AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionAirgapMostly AI
PricingPaid (tier details not public)Contact for pricing
DeploymentLocal only, air-gapped capableCloud or self-hosted (K8s/OpenShift)
Key FeatureOn-device document Q&A and summarizationSynthetic data generation (TabularARGN)
Best ForProfessionals handling confidential documentsData teams needing high-fidelity synthetic data
IntegrationsNone listedDatabricks, AWS, Snowflake, etc.
Recent UpdateNo recent newsDialogue-based workflow simplification (2025)

Pick Mostly AI if you need to generate synthetic versions of large datasets for ML or analytics, especially in cloud ecosystems like Databricks or AWS. Choose Airgap if your top priority is keeping confidential documents entirely on-device for chat and summarization—no cloud involvement. They solve different problems; decide based on whether your data is tabular and shareable (Mostly AI) or document-based and strictly private (Airgap).

Airgap
Airgap

Local document AI: query your PDFs, Markdown and text files with page-level citations — nothing leaves your machine.

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Mostly AI
Mostly AI

Generate privacy-safe synthetic data with MOSTLY AI's Apache v2 SDK and TabularARGN engine.

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Pricing
Paid
Contact Sales
Plans
—
—
Popularity
2 views
7.3k views
Skill Level
Intermediate
Beginner-friendly
API Available
Platforms
Desktop
WebAPI
Categories
❓ Document Q&A & Summarizing🔒 Security & Privacy📑 Document AI & Data Extraction
🏷️ Data Labeling & Training Data📊 Data & Analytics🔒 Security & Privacy
Features
Local document RAG over PDF, Markdown and text files
Page and paragraph citations linking answers to source
Source highlighting on cited passages
Portable, shareable vaults with a private per-vault vector index
Fully on-device pipeline — nothing uploaded to be indexed
Offline ingestion, retrieval and generation once models are cached
Five built-in local models: Llama 3.2, Qwen 2.5, Phi 3.5, Gemma 2
Bring your own GGUF model from any Hugging Face repository
Multilingual retrieval with a 100-language embedding model
Local inference via llama.cpp, models cached after one download
No hosted account, cloud workspace or relay between app and files
Vaults protected at rest by FileVault, BitLocker or LUKS disk encryption
Available for macOS, Windows and Linux
Optional connected-model mode (off by default) that sends questions to a hosted API
Works with Wi-Fi disabled for air-gapped environments
Privacy-safe synthetic tabular and textual data generation via TabularARGN
Apache v2 open-source Synthetic Data SDK, installed with pip install mostlyai
Multi-table synthesis preserving referential integrity across linked tables
Time-series and events data synthesis for relational and sequential datasets
Built-in differential privacy with temperature control for utility tuning
AI Assistant writes and runs Python code from natural-language prompts
Dialogue-based interface turning synthesis workflows into conversational steps (Nov 2025)
Mock data generation with relational coherence across linked tables (Oct 2025)
Simulated data for edge cases, what-if scenarios, and algorithm stress testing
Real-World Data mode surfaces insights from live systems like Databricks
100x faster generator training with automated training and sampling
Quality reports on trained generators plus conditional and seeded generation
Generate up to one million synthetic samples locally from a trained generator
Export trained generators to a file and upload to the platform for sharing
REST API and Python client for programmatic platform access
Integrations
Databricks
Snowflake
Google BigQuery
Azure Blob Storage
Google Cloud Storage
AWS S3
MariaDB
Microsoft SQL Server
MySQL
Oracle Database
PostgreSQL
Apache Hive

What real users say: Airgap vs Mostly AI

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

Airgap

50 mentions across 4 sources · 45% positive — mixed (averaged across 4 sources)

Hacker News, YouTube, Product Hunt, Lemmy

What users praise

  • • Truly local processing ensures data never leaves your device.
  • • Offline capability makes it useful for air-gapped environments.
  • • Ideal for regulated industries with strict compliance needs.
  • • No data residency concerns, appealing to global enterprises.

What frustrates them

  • • Very few user reviews limit confidence in reliability.
  • • Setup requires technical knowledge, despite beginner claim.
  • • On-device AI may lag on large or multiple documents.
  • • Pricing unclear; no free tier or trial mentioned.

Researched Aug 24, 2026

Mostly AI

No verifiable community signal. We scanned public discussion on Oct 14, 2026 and found posts matching the name “Mostly AI”, but could not establish that they are about this product rather than something else sharing its name. Rather than publish a score built on the wrong subject, we publish none.

Who should pick which

  • Data scientist at an enterprise using Databricks
    Pick: Mostly AI

    Needs high-fidelity synthetic data for ML training while preserving privacy; Mostly AI integrates directly with Databricks and AWS and supports multi-table synthesis.

  • Legal professional handling privileged case files
    Pick: Airgap

    Requires absolute confidentiality; Airgap processes documents locally, ensuring data never leaves the machine, ideal for attorney-client privilege.

  • Analyst needing natural-language data insights
    Pick: Mostly AI

    Mostly AI's AI Assistant with Python execution allows automated sampling and training via dialogue, reducing engineering effort.

  • HR manager with sensitive employee records
    Pick: Airgap

    Airgap provides on-device Q&A and summarization over HR documents without cloud risks, suitable for compliance.

  • Regulated industry user in air-gapped environment
    Pick: Airgap

    Airgap explicitly supports air-gapped environments, unlike Mostly AI which requires cloud or Kubernetes deployment.

Frequently Asked Questions

Airgap vs Mostly AI: which should you choose?

Pick Mostly AI if you need to generate synthetic versions of large datasets for ML or analytics, especially in cloud ecosystems like Databricks or AWS. Choose Airgap if your top priority is keeping confidential documents entirely on-device for chat and summarization—no cloud involvement. They solve different problems; decide based on whether your data is tabular and shareable (Mostly AI) or document-based and strictly private (Airgap).

Can Mostly AI handle unstructured documents like PDFs?

No, Mostly AI focuses on structured/tabular data synthesis, not document processing. For document Q&A, Airgap is the appropriate choice.

Does Airgap require an internet connection?

No, it works offline because models run on-device, making it suitable for air-gapped setups.

Is Mostly AI open-source?

It offers an open-source Synthetic Data SDK under Apache v2, but the full platform requires a paid enterprise license.

Can Airgap process scanned documents or images?

The listed features mention PDF, DOCX, and common formats—not OCR or images specifically. Check vendor for image support.

Which tool is better for generating mock data for development?

Mostly AI explicitly includes mock data generation for staging and testing, so it's the better fit.

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Last reviewed: August 24, 2026