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THEYknowIT Beaver Mascot

Your company's memory.
In Slack.

Slack · Jira · GitHub · Notion — searched simultaneously

Join the Waitlist → See How It Works

The Problem

Your team is bleeding time.

Your team's knowledge is scattered across four apps. Finding anything takes longer than building it again from scratch.

Frustrated beaver drowning in browser tabs

30-60 min/day searching

Developers context-switch across Slack, Jira, GitHub, and Notion every time they need an answer. The information exists. Finding it is the problem.

Beaver leaving with a glowing brain

The "Ask Wojtek" problem

Knowledge lives in people, not systems. When the senior dev goes on vacation (or leaves), years of context walk out the door.

Archaeologist beaver digging through documents

Decision archaeology

"I think we discussed this 6 months ago..." Now good luck finding which Slack thread, Jira ticket, or Notion page it's buried in.

Without THEYknowIT

💬 🎯 💻 📝
45 min
Searching 4 apps, pinging 3 people, giving up, rebuilding from scratch

With THEYknowIT

💬
15 sec
One question in Slack. Full answer with sources. Done.
166 hours/month
wasted on searching. 20 developers × 30 min/day = an entire dev gone.
🦫 Look, I'm a beaver. Even I can see this is broken.
# dev-questions
👨‍💻
Marek 10:42 AM
@THEYknowIT How does authentication work in Dam Management?
🦫
THEYknowIT APP 10:42 AM
Dam Management uses JWT-based authentication with refresh token rotation. The flow is:
// src/auth/middleware.ts
export const authMiddleware = (req, res, next) => {
  const token = req.headers['authorization'];
  const decoded = verifyJWT(token);
  req.user = decoded;
}
Sources: dam-management-backend/src/auth/ · DAM-234 · #backend-decisions (Jun 2025)

The Solution

One Slack message.
Done.

Ask a question in Slack. THEYknowIT searches all four sources simultaneously, synthesizes the answer, and cites every source. Your team never leaves Slack.

It reads actual code, finds the Jira ticket, pulls the Slack thread where the decision was made, and shows you the Notion doc. One answer with full context.

💬 Slack 🎯 Jira 💻 GitHub 📝 Notion
Smug beaver lounging in a gaming chair
🦫 Four apps searched. One answer returned. I'd high-five you but I have paws.

Differentiators

Why we're not like the other bots.

Multi-armed hacker beaver browsing code
01

Reads your actual code. Live.

Our agentic analyzer explores your GitHub repos in real-time using 6 specialized tools across up to 30 iterations. It browses files, searches patterns, maps dependencies.

The only Slack bot that browses your repo like a developer.
02

26-31% better search accuracy.

Hybrid BM25 + dense vectors with Reciprocal Rank Fusion, followed by Cohere neural reranking. Not just keyword matching — actual semantic understanding.

NDCG@10 improvement backed by retrieval research.
03

Self-correcting AI.

The system grades its own search results. If quality is too low, it rewrites the query and re-retrieves. No "I don't know" when the answer exists.

Automatic query rewriting with relevance grading loop.
04

Works in any language.

Built for multilingual teams from day one. Ask in the language your team actually uses and get the same grounded answers across docs, tickets, code, and chat.

Consistent retrieval quality across multilingual queries.
Other Slack bots search Slack. Groundbreaking. We search everything. Simultaneously. While reading your actual code. You're welcome.

Convinced yet? 🦫

Join the waitlist. Your team's collective memory is waiting.

Join the Waitlist →
🦫 Self-correcting AI that reads your actual code? Yeah, the other bots can't do that. We checked.

Under The Hood

The 9-stage pipeline.

Every question passes through 9 independently optimized stages. Each one matters.

Beaver engineer operating a massive steampunk pipeline machine
01
🧠
Intent
Classify query type
→
02
🔬
Embed
768-dim vectors
→
03
🔍
Search
BM25 + dense hybrid
→
04
🔄
Self-Correct
Grade & rewrite
→
05
📈
Rerank
Cohere neural
→
06
⚖
Weight
Importance scoring
→
07
📜
Format
Context + PII filter
→
08
⚡
Generate
Route to best LLM
→
09
🔗
Cite
Dedupe sources

Each stage independently optimized. Total latency: 5-15 seconds.

🦫 Nine stages sounds like a lot. It takes less time than your standup.

The Numbers

The receipts. Unredacted.

Data scientist beaver presenting charts
$74
Monthly operating cost
1,686%
Return on investment
10x
Cost savings from model routing
2,886
Documents indexed
4
Sources unified
9
AI agents working for you
<15s
Average response time
$0
Per query for embeddings
🦫 I did the math. I'm a beaver. Beavers are good at math. Trust me.

Smart Spending

We don't charge Porsche prices for a bicycle ride.

THEYknowIT runs on less than your team's monthly coffee budget. The answers stay sharp.

Instant
Quick answers
Under 5 seconds
  • "What's the staging URL?"
  • "Where's the onboarding doc?"
  • "Who owns the billing service?"
  • "What did we decide about caching?"
The stuff that shouldn't require pinging anyone.
Thorough
Deep dives
10–15 seconds
  • "How does auth work in the payments service?"
  • "Why did we switch from REST to gRPC?"
  • "Walk me through the deployment pipeline"
  • "What are the open blockers on the migration?"
The stuff that used to require a 30-minute meeting.
Your team's search tax
166 hrs/month Developer time lost searching
vs
$74/month THEYknowIT's total operating cost

That's less than half a day of contractor rates to save 166 hours.

Traffic controller beaver directing queries to different model lanes

"Your most expensive search engine is a senior developer's time. We're cheaper."

🦫 We're cheap where we can be and smart where we have to be. Just like real beavers.

Built Right

Your data stays yours.

Security guard beaver protecting a data vault
🔒

Self-hosted infrastructure

Deploy on your own servers. Qdrant and Redis run locally. No data leaves your perimeter unless you want it to.

🚫

PII sanitization built in

Sensitive data is redacted before it reaches any LLM. Names, emails, phone numbers — scrubbed automatically.

🔌

No vendor lock-in

Swap LLM providers, switch vector databases, replace any component. Every piece is modular and interface-driven.

Excited beaver with a glowing envelope

Stop searching.
Start asking.

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