HammerLock AI

Introduction to HammerLock AI

HammerLock AI is a privacy-first desktop AI assistant designed exclusively for macOS devices with Apple Silicon. It operates locally on the user's machine using the open-source OpenClaw framework and Ollama for local model execution. The application prioritizes data sovereignty by ensuring no user data is stored, processed, or trained upon by third-party servers unless explicitly opted into by the user. It targets professionals who handle sensitive information—including founders, legal counsel, financial advisors, compliance officers, and operational leaders—who require strict control over data residency, encryption, and processing.

The assistant integrates natively with Apple ecosystem services (Calendar, Reminders, Notes, Mail, iMessage), developer tools (GitHub), communication platforms (WhatsApp), smart home systems, and browser automation. All interactions are encrypted at rest using AES-256, and personal identifiable information (PII) is automatically scrubbed before any optional cloud-based query is dispatched.

Key Takeaways

• Runs entirely locally on Apple Silicon via Ollama; supports bring-your-own LLMs and optional cloud providers (OpenAI, Anthropic, Google, Groq, Mistral, DeepSeek)
• AES-256 encrypted storage for conversations, personas, uploaded files, and notes—no data leaves the device by default
• Automatic PII anonymization for all outbound queries to cloud APIs, with redaction and restoration handled locally
• 27 native integrations including Apple Calendar, Reminders, Notes, iMessage, Mail, GitHub, WhatsApp, smart home (Hue, Sonos), PDF analysis, and browser automation
• Eleven specialized AI agents (Strategist, Counsel, Analyst, Researcher, Operator, Writer, Coach, Money, Content, Director, and more) with domain-specific prompting and memory
• Brave-powered private web search with inline citations and PII scrubbing; no search history or identity exposed to providers
• Persistent local memory for personas, preferences, and SOPs—loaded per session and never synced externally

How HammerLock AI Works

HammerLock AI operates as a desktop application that installs directly on macOS. Upon first launch, users set an encryption password that is never transmitted or stored remotely—it serves solely as the key to decrypt local data. Users then select their preferred AI engine: either a local Ollama model (e.g., Llama, Phi, Gemma) or one or more cloud providers via API keys. The system employs parallel provider racing—sending queries simultaneously across configured providers—and returns the fastest valid response, with automatic failover if any provider is unavailable.

All input is processed through a local anonymization layer that identifies and removes PII (names, emails, phone numbers, addresses) before routing to cloud APIs; scrubbed tokens are restored in responses. Native skills execute locally via AppleScript and system APIs, while browser automation runs in an isolated, dedicated browser instance controlled from chat. Voice input uses on-device Whisper transcription; output can be rendered via TTS. Uploaded PDFs are parsed and analyzed locally, and all outputs—including markdown exports and vault entries—are stored encrypted on the device.

Core Benefits and Applications

HammerLock AI enables secure, compliant workflows across regulated and high-stakes domains. Founders and CEOs use it for competitive intelligence, investor deck drafting, and acquisition planning without creating external query logs. Legal professionals conduct privileged research, draft regulatory memos, and analyze case law while preserving attorney-client privilege. Financial advisors model portfolio exposure, summarize earnings calls, and prepare client reports without exposing confidential financial data to third-party models. Operators load internal SOPs, market research, and team personas to maintain contextual continuity across projects without broadcasting proprietary knowledge. Healthcare, government, and enterprise users deploy it for HIPAA-compliant document analysis, air-gapped intelligence support, and internal knowledge base querying—all without cloud dependency.

Pricing tiers include a Free plan (open source, self-hosted, GitHub-distributed), Core ($15 one-time), Pro ($29/month), Teams ($49/user/month), and Enterprise (custom on-premise). Optional Booster and Power Packs add cloud AI credits, but users may also supply their own API keys for unlimited access without markup.