Sound Software Development is a Phoenix, Arizona software engineering team delivering national projects in custom software development, AI integration, and LLM platform implementation. This page documents how we ship production systems centered on LoRA / PEFT Fine-Tuning & Custom LLM Adaptation—not slide decks—across TypeScript, Python, React, Next.js, FastAPI, Node.js, PostgreSQL, AWS, Docker, and modern CI/CD.
We align fine-tunes with evaluation gates before any customer-facing rollout. Teams engage us when internal prototypes using ChatGPT-style UIs must evolve into authenticated, multi-tenant products with OAuth, RBAC, observability, and SLAs. We map your stakeholders—product, security, IT, marketing—and deliver incremental milestones you can ship behind feature flags.
Engagements include architecture reviews that map data residency and compliance expectations to hosting choices—managed APIs versus self-hosted LLaMA 3 or Mistral on private AWS EC2 or Kubernetes—and runbooks your SRE team can operate after launch, including credential rotation for Twilio, Stripe, and cloud providers.
Across the stack we integrate Claude (Anthropic), GPT-4o, GPT-4, GPT-3.5 Turbo, Gemini 1.5 Pro, LLaMA 3, Mistral, Mixtral, Cohere Command R+, Falcon, and BLOOM where appropriate; orchestrate with LangChain, LangGraph, AutoGen, CrewAI, OpenAI Assistants API, Anthropic Tool Use, MCP, and Semantic Kernel; embed with OpenAI Embeddings and Sentence Transformers; index in Pinecone, Weaviate, Chroma, pgvector, and FAISS; and operate with prompt engineering, RAG, LoRA/PEFT fine-tuning, LangSmith, Weights & Biases, and Hugging Face Hub. Programming languages include JavaScript/TypeScript, Python 3, SQL, Bash, HTML5, CSS3/SCSS, R, and MATLAB handoffs. Frameworks span React 18, Next.js 14, Vue 3, Tailwind CSS, ShadCN/UI, Vite, Webpack, Node.js/Express, FastAPI, Flask, Django REST, tRPC, GraphQL, and REST. Automation covers Puppeteer, Playwright, Selenium, n8n, Make, Zapier, Robocorp, PyAutoGUI, OpenAI Assistants, and cron schedulers. Data stores include PostgreSQL, MySQL, MongoDB, Supabase, Firebase/Firestore, Redis, and SQLite. Cloud & DevOps span AWS (Lambda, S3, EC2, RDS, SES), Vercel, Railway, Render, Docker, and GitHub Actions. Integrations include Gmail API, Google Calendar/Drive, Twilio, Stripe, HubSpot, Salesforce, DocuSign, QuickBooks Online, and SendGrid—all relevant when extending LoRA / PEFT Fine-Tuning & Custom LLM Adaptation into a complete product surface.
AI infrastructure & MLOps around LoRA / PEFT Fine-Tuning & Custom LLM Adaptation
Prompt engineering is not guesswork when paired with eval datasets: we capture baseline scores, run A/B prompt variants, and gate releases. RAG pipelines receive chunk-size sweeps, reranker comparisons, and citation audits. Fine-tuning with LoRA / PEFT on LLaMA 3, Mistral, or domain corpora uses the Hugging Face Hub for weights, Weights & Biases for experiment tracking, and hardened inference on vLLM or cloud GPUs.
We align fine-tunes with evaluation gates before any customer-facing rollout. LangSmith traces tie user sessions to chain steps for support and compliance. We deploy training and batch jobs with Docker, schedule them via GitHub Actions or AWS Lambda, and store artifacts in S3 with lifecycle policies. Python remains the default for HF/transformers; TypeScript orchestrates edge and Vercel routes.
Related stack keywords: LoRA, PEFT, fine-tuning, Hugging Face, LLaMA, Mistral, Weights Biases, custom LLM.
Comprehensive synthetic checks and production-like canaries—scheduled with GitHub Actions, cron, or AWS Lambda—verify that releases touching LoRA / PEFT Fine-Tuning & Custom LLM Adaptation still meet latency and quality SLOs after SDK upgrades, index rebuilds, or prompt template edits, with rollback paths tested in Docker and staging environments before customer traffic shifts.
Security, compliance & evaluation
We treat prompts, tools, and retrieval sources as attack surface: least-privilege database roles, secrets managers, VPC isolation for self-hosted LLaMA 3 / Mistral inference, and red-team prompts for jailbreak resistance. For regulated workflows, we document data flows for HIPAA-style or financial reviews, integrate DocuSign for consent, and avoid training on customer data unless contractually explicit. Evaluations combine automated checks (JSON schema match, embedding distance to gold answers) with human review queues.
Why Sound Software for LoRA / PEFT Fine-Tuning & Custom LLM Adaptation
You get senior engineers who have shipped LangGraph agents, OpenAI Assistants file search, Anthropic tool loops, Gemini multimodal features, Pinecone namespaces, and Stripe metered billing in the same codebase—without throwing away your existing Salesforce or HubSpot investments. We document runbooks, hand off repositories with tests, and align roadmaps to measurable KPIs (deflection rate, time-to-answer, ARR impact).
Explore the full expertise library, AI services, AI technology overview, or contact us for a scoped statement of work. Canonical expertise URL: /expertise/lora-peft-fine-tuning-llm/.