The Silo Problem
Every team I've worked with keeps its knowledge in eight or more tools. The decision lives in a Confluence page, the reasoning in a Slack thread, the contract in DocuSign, the code in GitHub, and the context in someone's inbox.
The AI features bolted onto each of those tools only see their own silo. Notion AI knows Notion. Confluence AI knows Confluence. Nobody's AI can answer a question whose answer is spread across all of them, which is most of the questions that matter.
What Teams Actually Do
- Dig through dozens of pages to find one decision
- Ask the one person who remembers, and wait
- Migrate everything into yet another tool, creating a new silo
- Paste documents into a public chatbot and hope nothing sensitive leaks
RetrieveIT takes the opposite approach: leave the knowledge where it lives. Connect your tools with OAuth, ask a question in plain English, and get an answer with citations back to the source documents.
Part 1: Six Days to Launch
I registered retrieveit.ai on December 31, 2025. Six days later it was a production SaaS with real users and real payments. Not a demo. I built it solo, with OutcomeOps and Claude Code, following architecture decisions I had already written down.
The Launch Week
Domain + Core Auth
Registered retrieveit.ai. Multi-tenant auth with passwordless magic links working by midnight.
Search + Workspaces
Semantic search on Bedrock. Multi-tenant workspaces. Conversation memory.
Integrations + Billing + CI/CD
GitHub, Google Drive, and Gmail over OAuth. Stripe subscriptions. Automated tests and a GitHub Actions pipeline.
Launch
Marketing site live. App deployed through CI/CD. First signups within hours.
Not a Hackathon Project
Fast didn't mean cutting corners. These were in place from day one, because the patterns were already documented:
A consultancy would quote three to six months for that scope. The difference wasn't typing speed. It was zero architecture meetings, because every pattern the AI needed was already an ADR it could query.
Part 2: Twenty Connectors, One Pattern
Federated search lives or dies on integrations, and integrations usually sprawl. Every vendor has its own auth flow, pagination quirks, download semantics, and retry behavior. Without discipline, the twentieth connector takes longer than the first.
Two architecture decisions kept that from happening.
ADR-001: Workspace-Scoped Tokens
OAuth connections belong to a workspace, not an organization. Legal and engineering in the same company can connect different Gmail accounts without colliding. Most enterprise search products scope to the org, which is why they stall at one team.
ADR-002: One Shared Ingestion Pipeline
Eleven connectors had grown eleven copies of download, upload, and embed logic. One shared ingestion Lambda took it over. Each new connector now only enumerates files and enqueues them.
The effect is measurable. The first eleven connectors took about 2.4 days each. After ADR-002, each new connector took about a day. RetrieveIT now connects to twenty tools:
Part 3: Built for Regulated Buyers
The people with the worst silo problems are law firms, healthcare organizations, insurers, and financial services teams. They are also the ones who can't send their documents to just any vendor. So the architecture was designed for the security review from the start.
The Platform
AWS S3 Vectors
Vectors live in AWS alongside the documents they describe. No third-party vector SaaS, no extra vendor in the data path.
Claude on Bedrock
Retrieval-augmented answers with citations, served through Bedrock under the same trust model as the rest of the stack.
Isolation at the Index
Every vector query is filtered by organization and workspace at the index level. Isolation is a primitive, not a post-filter.
Tokens That Survive a Review
OAuth tokens KMS-encrypted at rest, rotated on every use. Magic-link sign-in, so there are no passwords to phish.
Query Content Not Stored
Only metadata is logged. The question and the answer never persist.
MCP Server Included
Claude Desktop, ChatGPT, Cursor, and other AI tools can query a workspace directly over MCP.
The Proof
RetrieveIT is a product, and it's also the strongest evidence for OutcomeOps. Every connector, every isolation rule, and every security pattern was written by AI that queried my documented standards first. The same methodology I take into enterprise engineering teams built this platform, solo, in production.
"The patterns aren't the marketing. They're the moat."
Document the shape once, and every connector after the first inherits it.