Project knowledge scattered across tickets, wikis, ADRs, PDFs and chat threads caused slow onboarding (1-2 weeks) and 30-120m delays for routine answers; teams spent more time 'knowledge hunting' than building.
Centralized, per-client isolated AI knowledge engine indexing all project history (tickets, docs, ADRs, chats, imports) and delivering cited natural-language answers, instant collective memory & 24/7 self-service—powered by secure, granular opt-in access control and strict data segregation.
Software projects build a vast history, but that information rarely stays in one place. Over time, this critical knowledge can get scattered and siloed.
As projects evolve, teams naturally change on both the client and developer side. It becomes impossible for anyone to remember every detail.
Here are the most common challenges we see and how we solve them.
Your project's history is spread out. There's a wiki, technical docs, hundreds (or thousands) of tickets, and countless chat messages. Even if it's all "documented," finding the one specific answer you need is like finding a needle in a haystack.
💡 Our Solution:
A Centralized Knowledge Engine
It connects to all of it. It indexes your tickets (descriptions, comments, status), your wikis, your technical docs, and even PDF uploads. It reads everything, so you don't have to. It's not just a "search"—it uses an AI model to understand context, connect the dots, and find the real answer.
You have a question about a feature's history, but the lead developer is in a meeting or working on a critical task. You're blocked, and you have to wait for someone to dig up the answer for you.
💡 Our Solution:
24/7 Self-Service Answers
Our AI assistant gives you instant, self-service access. You can ask it natural language questions in a private chat (like, "What was the last update on the 'Menu Caching' ticket?") and get a clear, documented answer in seconds. It's like having a project historian on call 24/7.
It's normal for teams to change over the years. But how do you get a new Product Owner or stakeholder up to speed on a project with a two-year history? It can take weeks of reading and meetings.
💡 Our Solution:
An Instant "Collective Memory"
It acts as the project's memory. A new team member can ask it to "summarize the high-level architecture for user restrictions," and it will provide a clear, bullet-pointed summary. This turns weeks of onboarding into hours.
This is the big one. Every hour a developer (or you) spends searching for an old configuration setting or decision is an hour not spent building the next valuable feature. That's a direct cost to your business.
💡 Our Solution:
Focus on What Matters
By providing instant, accurate answers, we unblock everyone. This lets the entire team focus on what really matters: moving your business forward by shipping new features, improving performance, and hitting your goals.
This is why we built our AI-power Project Assistant.
The core idea is to gather all that scattered data into one place and make it accessible using natural language.
It's not just a simple search or another chatbot, it is a powerful knowledge engine.
We use a Large Language Model (LLM) that can read between the lines, connect the dots, and search through the entire project history incredibly fast.
This process transforms a passive, fragmented archive of data into an active, intelligent partner you can actually talk to.
The AI Project Assistant connects to and indexes a wide array of data for each project:
We make it accessible through the platforms our teams and clients already use.
In-Messenger Chat: For us, offering it as a Slack App was the most convenient first step. This is currently the primary access point.
The AI Project Assistant is already demonstrating significant value. In the end, it lets everyone focus more on moving the business forward—working on what really matters like new features, performance, and strategy—rather than getting stuck searching for information.
Screenshot of a real world chat with AI assistant. Click to enlarge!
Instant, 24/7 Self-Service: Clients can get answers to common questions about a feature's history or a ticket's status without having to wait for a developer.
Transparency: By making project history searchable, we're providing a new level of transparency into the work and decisions.
Faster Onboarding: When we take over a project, we can feed its history into the AI Project Assistant, making our team effective from day one.
Client Statement: "As a Product Owner, I love that I can ask for a summary of a complex feature and get a clear, documented answer right away. It's like having a project historian on call 24/7."
Reduced "Knowledge Hunting": Developers get unblocked faster and spend less time digging for information.
Cross-Project Insights: Developers can query the "collective memory" of the entire agency (with access restrictions, of course).
Better Onboarding: New team members can get up to speed on a long-running project in hours, not weeks.
Developer Statement: "Finding that one specific configuration we were missing would have taken hours of digging through documentation and tickets. The bot found it in seconds. This unblocked my task immediately."
We can't stress this enough: security and data privacy are paramount. We built the AI Project Assistant with a strict, opt-in access model from the ground up.
The AI Project Assistant is a living tool, and we're actively expanding its capabilities. We really are excited about what's next. Our roadmap is focused on deeper integrations and broader access.
New Access Channels (Slack was just the first step.)
Deeper Data Integrations:
Proactive & Automated Insights:
Book a 30-minute call where we assess your current knowledge challenges and demonstrate how our AI knowledge engine can reclaim hours for your team.
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