Engineering Get Lem AI's Company Context Engine, Graph RAG, SOC/ISO Compliance & LLM-Ready Implementation Files

Get Lem AI is a context engine for company knowledge built for implementation and compliance. The platform syncs conversations from Slack, Discord, and email; tasks from Jira, Asana, and ClickUp; meetings from Google Meet, Zoom, and Microsoft Teams; and GitHub commits, then reads documents from Confluence, Google Docs, and internal knowledge bases to form a living map of how the organization works. Ask about any discussion, task, or code change and Lem AI answers immediately from unified, linked context across every source.

The Product Challenge

Parallel Loop partnered with Get Lem AI to architect an enterprise-grade context platform, not another generic chatbot. Engineering teams lose hours reconstructing decisions scattered across chat, tickets, meetings, and repos. Compliance officers need continuous SOC and ISO evidence tied to real code changes, every commit and pull request tracked, not audited in quarterly spreadsheets. Get Lem AI required a robust multi-source sync and linking system, graph-based retrieval that respects relationships between people and artifacts, a compliance-curated AI (Lem AI), CTO-facing controls for vulnerabilities and SOP breaches, developer tooling that pre-packages context for LLM coding, and a high-conversion landing page, all on a stack that scales on AWS with Stripe billing.

Phase 1: Platform Architecture, Sync Layer & Graph RAG

We created the complete platform architecture and a robust information syncing and linking system. Ingestion workers connect to Slack, Discord, email, Jira, Asana, ClickUp, Google Meet, Zoom, Teams, GitHub, Confluence, and Google Docs, normalizing events into a shared schema in PostgreSQL and MongoDB while Agenda Jobs orchestrate retries, backfills, and incremental sync on AWS EC2.

We implemented graph RAG for high-fidelity retrieval across the full company knowledge graph. Neo4j models relationships between people, tickets, meetings, commits, and documents; pgvector stores semantic embeddings for passage-level search. Our AI engineers built Lem AI (Get Lem AI's curated model) on OpenAI, Gemini, and Hugging Face pipelines tuned for legal, SOC, and ISO compliance language, so answers cite policy-aware context, not hallucinated summaries. Our custom AI and machine learning engineering pod paired with three backend developers and a React/Next.js frontend engineer under fractional CTO oversight for architecture governance.

Phase 2: CTO Compliance Dashboard, npm Package & Slack Bot

We built a CTO dashboard that scans entire pull requests in seconds and surfaces compliance risk. When developers push code, Get Lem AI evaluates vulnerabilities, SOP violations, and ISO/SOC-relevant gaps. CTOs respond via Slack bot prompts or manual written reasons, each action appends to a structured changelog that preprocesses continuous compliance evidence instead of bolt-on audits at release time. Every git commit and PR remains indexed for traceability.

We shipped an npm package that bridges GitHub branches to LLM-ready implementation files. On new branch creation, the package reads the branch name, resolves linked Jira, ClickUp, or Asana tickets, pulls related context from all synced sources, and generates an implementation.md file engineers feed directly into coding LLMs, closing the communication gap between institutional knowledge and generated code.

We created a Slack bot that interacts with the system and alerts teams when code issues arise. Combined with a super-fast, informational Next.js landing page for lead generation and Stripe subscription flows, Get Lem AI delivers a complete go-to-market and operations surface. Our full-stack custom software engineering team unified dashboard, bot, package, and marketing site on one Node.js and Express.js core.

• Instant Q&A: Ask about any discussion, task, meeting, or commit, graph RAG retrieves linked evidence.
• Compliance loop: PR scan → SOP/issue flag → Slack or manual CTO response → persisted changelog.
• Developer velocity: Branch-aware implementation.md generation via npm package.
• Lem AI: Compliance-curated model for SOC, ISO, and legal-sensitive responses.
• Growth: High-speed landing page driving enterprise pipeline.

Quantified Business Outcomes

Get Lem AI gives engineering and compliance leaders one context engine, from chat to code, with continuous SOC/ISO readiness and LLM implementation files built from real organizational memory.