Full-stack AI developer to set up a secure local GPT-like assistant with doc analysis and memory.
Seeking a highly competent AI engineer to build a fully local, modular AI assistant designed for legal analysis, document synthesis, clinical planning, and research-intensive writing. This is a mission-critical cognitive environment, not a chatbot or LLM toy.
The system must run entirely offline, preserve compartmentalized memory, and support vector-based document ingestion — all deployed on a MacBook Pro M4 Max (64GB RAM, 2TB SSD). It must be auditable, inspectable, and fully under user control at every layer.
Build Scope (Three Phases – One Builder Only)
You will be contracted to deliver the entire architecture across three phases:
Phase 1 — ("Legal & Tax Office")
• LM Studio / llama.cpp optimized for Apple Silicon
• Vector DB setup (Chroma/Qdrant/Weaviate) with local document parsing
• UI (Streamlit, Electron, or lightweight shell)
• PDF/DOCX ingestion with embedded citation + source trace
• Memory persistence: prompt saving, tone tagging, output control
• Output styles: affidavit, brief, memo, etc.
• No cloud sync. No logging. Fully local.
Phase 2 — ("The Board Room") Multi-Domain Strategic Workspace
• Add support for clinical workflows, estate planning, strategic writing
• Improved memory containers (per domain)
• API access wrapper to GPT-4 or Claude 3 (via user-owned keys ONLY)
• Enhanced persona switching, tone locks, exportable sessions
Phase 3 — ("The Den") Private Cognitive Module
• Separate vault for high-context reasoning and longform writing
• Firewalled from Office; no cross-contamination
• Persistent memory, stylistic voice preservation, session archiving
• Local-only inference with optional narrative assistive tools
• Optional future integration: multimodal parsing, encryption layers
Security & Audit Clauses (Non-Negotiable)
• You must consent to third-party code audit after each phase
• No proprietary wrappers
• No API calls unless explicitly declared and authorized
• All configuration paths, prompts, vector stores, and memory logs must be accessible to the user
• You will provide:
• Full install scripts
• Summary.txt documenting build logic, parameters, dependencies
• Notes to replicate install from clean OS
Payment Structure
This is an hourly project with a firm "not-to-exceed" ceiling, payable at the end of each phase upon satisfactory completion and code audit.
Terms:
• You (the builder) are committing to the entire 3-phase build, unless mutually terminated.
• I (the client) commit to paying for each completed phase promptly and fully once:
• Deliverables are met
• The audit review is cleared
• I reserve the right to end the project after any phase, for any reason, without obligation to proceed further.
• You agree that no partial or hidden ownership exists — all build components, logic, and configuration must be shared in full and are under the client’s control.
Summary:
PhaseDeliverable Payment Exit Clause
Phase 1 Inference + UI Paid after audit Client may exit
Phase 2 Vector Store + API logic Paid after audit Client may exit
Phase 3 Final Memory Shell + Vault Split Paid after audit Final
Please submit your hourly rate and your not-to-exceed cap (USD) for the full build.
System Context
You’ll be working on a clean Apple M4 Max MacBook Pro (64GB RAM, 2TB SSD), macOS Sonoma.
Pre-installed:
• LM Studio
• Homebrew
• Git
Available access:
• AnyDesk (if needed)
• Local data files (legal PDFs, notes, DOCXs, etc.)
Preferred Stack (flexible with reasoned alternatives)
Layer Preferred Tool
Inference LM Studio / llama.cpp
Vector DB Chroma or Qdrant
File Parsing PyMuPDF, unstructured.io
UI Streamlit or Electron
Memory Logic JSON store or LangGraph
API Gateway (Phase 2–3) GPT-4/Claude via secure keys
Models to install/test:
• MythoMax 13B Q5
• Chronos Hermes 13B
• Mistral 7B Instruct (Final quantization/tuning TBD based on your advice)
✅ You Should Apply If You:
• Have built secure local GPT-style systems before
• Know vector stores, LLM inference, and UI wiring well
• Understand data compartmentalization
• Are comfortable being audited
• Can document your work cleanly
• Are discreet and professional in high-trust builds
Bonus if you’ve worked with:
• Apple Silicon
• Clinical/legal data environments
• High-context cognitive tools (not just chat interfaces)
How to Apply
In your message, please include:
1. A short list of similar builds (esp. local/private GPT)
2. Your preferred stack and why
3. Your hourly rate
4. Your not-to-exceed ceiling for all three phases
5. Confirmation you accept the audit clause and early termination terms
Apply Now
Apply Now
The system must run entirely offline, preserve compartmentalized memory, and support vector-based document ingestion — all deployed on a MacBook Pro M4 Max (64GB RAM, 2TB SSD). It must be auditable, inspectable, and fully under user control at every layer.
Build Scope (Three Phases – One Builder Only)
You will be contracted to deliver the entire architecture across three phases:
Phase 1 — ("Legal & Tax Office")
• LM Studio / llama.cpp optimized for Apple Silicon
• Vector DB setup (Chroma/Qdrant/Weaviate) with local document parsing
• UI (Streamlit, Electron, or lightweight shell)
• PDF/DOCX ingestion with embedded citation + source trace
• Memory persistence: prompt saving, tone tagging, output control
• Output styles: affidavit, brief, memo, etc.
• No cloud sync. No logging. Fully local.
Phase 2 — ("The Board Room") Multi-Domain Strategic Workspace
• Add support for clinical workflows, estate planning, strategic writing
• Improved memory containers (per domain)
• API access wrapper to GPT-4 or Claude 3 (via user-owned keys ONLY)
• Enhanced persona switching, tone locks, exportable sessions
Phase 3 — ("The Den") Private Cognitive Module
• Separate vault for high-context reasoning and longform writing
• Firewalled from Office; no cross-contamination
• Persistent memory, stylistic voice preservation, session archiving
• Local-only inference with optional narrative assistive tools
• Optional future integration: multimodal parsing, encryption layers
Security & Audit Clauses (Non-Negotiable)
• You must consent to third-party code audit after each phase
• No proprietary wrappers
• No API calls unless explicitly declared and authorized
• All configuration paths, prompts, vector stores, and memory logs must be accessible to the user
• You will provide:
• Full install scripts
• Summary.txt documenting build logic, parameters, dependencies
• Notes to replicate install from clean OS
Payment Structure
This is an hourly project with a firm "not-to-exceed" ceiling, payable at the end of each phase upon satisfactory completion and code audit.
Terms:
• You (the builder) are committing to the entire 3-phase build, unless mutually terminated.
• I (the client) commit to paying for each completed phase promptly and fully once:
• Deliverables are met
• The audit review is cleared
• I reserve the right to end the project after any phase, for any reason, without obligation to proceed further.
• You agree that no partial or hidden ownership exists — all build components, logic, and configuration must be shared in full and are under the client’s control.
Summary:
PhaseDeliverable Payment Exit Clause
Phase 1 Inference + UI Paid after audit Client may exit
Phase 2 Vector Store + API logic Paid after audit Client may exit
Phase 3 Final Memory Shell + Vault Split Paid after audit Final
Please submit your hourly rate and your not-to-exceed cap (USD) for the full build.
System Context
You’ll be working on a clean Apple M4 Max MacBook Pro (64GB RAM, 2TB SSD), macOS Sonoma.
Pre-installed:
• LM Studio
• Homebrew
• Git
Available access:
• AnyDesk (if needed)
• Local data files (legal PDFs, notes, DOCXs, etc.)
Preferred Stack (flexible with reasoned alternatives)
Layer Preferred Tool
Inference LM Studio / llama.cpp
Vector DB Chroma or Qdrant
File Parsing PyMuPDF, unstructured.io
UI Streamlit or Electron
Memory Logic JSON store or LangGraph
API Gateway (Phase 2–3) GPT-4/Claude via secure keys
Models to install/test:
• MythoMax 13B Q5
• Chronos Hermes 13B
• Mistral 7B Instruct (Final quantization/tuning TBD based on your advice)
✅ You Should Apply If You:
• Have built secure local GPT-style systems before
• Know vector stores, LLM inference, and UI wiring well
• Understand data compartmentalization
• Are comfortable being audited
• Can document your work cleanly
• Are discreet and professional in high-trust builds
Bonus if you’ve worked with:
• Apple Silicon
• Clinical/legal data environments
• High-context cognitive tools (not just chat interfaces)
How to Apply
In your message, please include:
1. A short list of similar builds (esp. local/private GPT)
2. Your preferred stack and why
3. Your hourly rate
4. Your not-to-exceed ceiling for all three phases
5. Confirmation you accept the audit clause and early termination terms
Apply Now
Apply Now