An AI that knows what your company knows, and tells you before you ask.

AE Studio builds AI knowledge management systems for enterprises. We connect your chat, meetings, documents, code, tickets, and CRM into one layer people and agents can query, with your permissions intact and every answer cited. Each week it also writes you a brief on what is happening and why. It runs in your cloud, and you own it.

Start with an AI readiness assessment Talk to an engineer

The assessment runs about 3 weeks and ends with a ranked list of what to build.

We run this system ourselves across roughly 150 people. Our delivery leads manage 3x the workload, and the system we build for you is the one we run every day.

Three tools, two meetings, one question.

Someone asks whether Project X is on track. You open the sprint board, then the budget sheet, then the Slack channel, then you message the PM who was in the standup, and forty minutes later you have an answer nobody wrote down. Next week someone else asks the same question and spends the same forty minutes.

That loop runs in every department, every week. And the answers that never get written down leave with the people who knew them.

McKinsey finds 88% of organizations now use AI regularly in at least one function, and 6% see more than 5% EBIT impact from it. The model is not the bottleneck. What the model can see is.

Connecting tools one at a time does not fix it either. Each tool returns its own schema and its own identity model, so Jordan in Slack is a stranger to Jordan in the meeting transcript, and the AI spends its context window rediscovering connections on every query.

Fix what the model can see, and a competent model beats a brilliant person who only has their own inbox.

Ask once. Get the answer, with citations.

AE Studio builds one layer over everything your organization produces, with people, projects, and decisions resolved once, ahead of any query. A person is already linked to their projects, meetings, messages, code, and time entries, so the question gets answered in a single pass, with citations back to the standup transcript, the sprint board, and the budget.

AE.STUDIOKNOWLEDGE MANAGEMENT

YOU ASK

"A prospect wants a six-month engagement. Should we take it, and what do we know about them?"

IT ANSWERS

• The deal. In conversation since March, scope well defined, two rounds of technical validation complete.
• The risk. Their last funding round was fourteen months ago with no announcements since, and on the last call their VP of Engineering mentioned being "thoughtful about runway."
• Capacity. The team with the right skills rolls off another engagement in July.
• Recommendation. Take it, with monthly milestones and payment terms that signal early if their cash tightens.

YOU ASK

"I missed this week's standups on the Acme project. What happened, and is there anything I need to act on?"

IT ANSWERS

• Good news. User acceptance testing passed on Wednesday, and the client's VP of Product called the pipeline "the first thing that actually works on our messy data."
• Open risk. Load testing was raised by the client's technical lead in all three standups, the third week running, and there is no plan for it in the sprint backlog.
• Act on this. Get a load testing session scheduled before the next sprint. That technical lead is your internal champion, and three weeks of an unanswered concern is how a champion becomes a skeptic.

Illustrative. The figures are fictional; the structure of the answers is real.

For us the unit of work is the client engagement. For you it might be the customer account, the plant, the program, or the patient, and the system is modeled around yours.
All five questions, and the architecture behind the answers →

The weekly brief doesn't wait to be asked.

Your tools record everything, and nobody pulls it together. So on a fixed cadence, it reads every connected source and writes a brief on what is happening and why, routed to the person who can act. Each recommendation arrives with four things.

• The evidence behind it, cited.
• What we expect to happen if you act.
• How you will know whether it worked.
• Whose call it is.

It drafts the email, the agenda, or the talking points too, so the owner opens the kit with the work mostly done. Next cycle it checks whether the action worked and learns from the ones that did not.

AE.STUDIOWEEKLY BRIEF

Acme CorpNeeds attention

Load testing blocker unresolved for three weeks. User acceptance testing on the document pipeline passed. Budget tracking ahead of plan from unscoped sprint work.

Action: High

Schedule a load testing planning session with the client's technical lead before the next sprint.

Execution kit: Meeting agenda

Attendees, timings, and exit criteria, ready to send.

OWNER: PROJECT MANAGER

One card from a week of output. The figures are fictional; the format is what our leadership reads every week.
See a full week of output →

Three of the things ours watches for. Yours will be different, and AE Studio designs them with you.

• Early warning. A client's mood has been sliding for three weeks across Slack, transcripts, and response times, and the account owner hears about it before the client escalates.
• Connection discovery. Two departments are paying different vendors for the same problem, and it says so, with the saving.
• Resource intelligence. Budget burn is running ahead of plan, traced to scope nobody re-estimated, with the re-scoping conversation already drafted.

And when you let it, it acts.

The same layer that answers people also serves your agents and automations, through the same interface, so the agent that answers a question can also update the record. When it does, the write goes back into your systems of record, logged and auditable.

Start with answers, add the brief, then let agents act on what the brief found. Which agents, and what they are allowed to do, is designed with you.
Read how we build AI agents →

What you get.

Everything below is built around your business and belongs to you.

• One queryable layer over every system your teams already use, with people, projects, and decisions resolved once.
• A cited answer to every question, traced to the message, transcript, or record it came from, and a plain "no source" when there is none.
• A weekly brief built around the decisions your leadership makes, with each recommendation routed to its owner and the email or agenda already drafted.
• Agents built for your workflows, acting through the same governed, logged path.
• The best model for each job, frontier or open-weight, swapped as better ones ship, so the system gets smarter without a rebuild.
• A first slice in weeks, built around one question your team keeps asking and grown source by source.

AE Studio does not start with a data platform. The first version connects the two or three sources behind one question your team keeps asking, ships in weeks, and earns the next source by being useful. Nothing gets connected that you did not choose, and when the system cannot cite a source, it says so.

Here is what it has done for the company that built it.

We built it for ourselves first.

IN-HOUSE

AE Studio

We run this system across our own projects, deals, and people, and it is how we hit the edge cases before your rollout does. Our delivery leads manage 3x the workload they carried before it, and our project managers run 50% more projects concurrently. Each of them gets back at least 15 hours a week that went to collecting status, flagging project risk, conducting research, and routing it all up the chain.

3x the workload per delivery lead

50% more concurrent projects per PM

15 hrs a week returned to each of them

These are our own operating numbers.

CLIMATE RISK

Jupiter Intelligence

We gave the climate-risk platform's global teams and clients conversational access to its data without writing raw queries.
Read the case →

Built for exactly what you need.

Nothing here comes off a menu. What a hospital group needs watched is not what a logistics company needs watched, so we model the sources, the brief, and the agents around your questions, your decisions, and your limits.

You also define what a good answer and a useful brief look like before we build. The system is checked against that definition, so you can see that it works the way you want.

Swipe sideways to see all columns.

Your data, your rules.

A system that reads everything your company produces has to be held to a higher standard than the tools it connects to. AE Studio builds AI knowledge management to that standard.

• It runs in your environment. The system and everything it holds run in accounts you own, alongside the systems you already have. Nothing gets replaced, and nothing leaves.
• Access mirrors your permissions. People and agents see only what they are already entitled to see in your source systems. For example, the version of the brief leadership reads can include team dynamics while the version the team reads leaves them out.
• Every fact is traceable. Each thing it knows is linked to the document, message, or record it came from, and dated. When something is corrected, the history is kept, so "what did we know about this project in March?" still gets an accurate answer.
• Every action is logged. Agents act within limits you set, and the record of what they did, what they recommended, and who approved it is yours to audit.
• You own what is built. Your data, your knowledge graph, your use cases, and the code behind them are yours.

AE Studio is a product and engineering studio of about 150 people that has built custom software and AI systems for enterprises since 2016. That includes government agencies and healthcare companies, where safe and secure systems are the baseline, so permission-aware design is normal work for us. An assistant that flattens permissions is a breach with a chat interface.

Questions buyers ask.

Is this AI knowledge management, enterprise search, or RAG?

All three describe parts of it. Enterprise AI search is the front door, enterprise RAG (retrieval over your own documents) is one of the techniques underneath, and AI knowledge management is the whole system, one permissioned layer that people and agents query, with cited answers and a weekly brief on top. The difference from enterprise search software is that you own the layer and agents can act through it.

How is this different from Glean or Copilot?

Glean, Agentspace, and Copilot are strong products for search and summaries across the tools they connect, and if that covers your needs, buy one. We are not the right fit for a standard rollout with ordinary permissions. This is the alternative you own, modeled to your permissions and your workflows, with a brief built around your decisions, agents that act within limits you set, and the model underneath swappable as better ones ship.

Will it respect our permissions, and where does our data live?

Yes, structurally. Who can see each piece of information is recorded when it enters the system and enforced on every question, so a person or agent only ever gets back what their role could already see. The data and the system stay on your infrastructure or in your cloud tenancy, with nothing in a shared multi-tenant product, and retention follows your policy.

What about hallucinations?

Every answer carries citations to its source material, and when the system cannot cite a source, it says so. Claims trace back to the original message, transcript, or record, so anyone can challenge and verify an answer. As part of our alignment research, we study the ways an assistant goes wrong, like sycophancy and selective disclosure, and those findings shape how we build and test every knowledge management system.

Which model does it use?

A combination of frontier models by default, with the best fit chosen for each job. We build the system against evals, independent of any one vendor, so when a better model ships we can upgrade to it and prove the quality held. The same evals let you run open-weight models where you prefer them.

How long until it is useful?

The first slice of the knowledge management system is useful in weeks because AE Studio starts it around one question your team keeps asking. It grows source by source from there, provided your security team grants read access to the sources and someone on your side owns the decision. Without those two, a build stalls in review.

What does it cost?

It depends on the sources, the permission model, and where it runs. We scope it with you during the AI readiness assessment, which runs about 3 weeks, and you have the full number before anything gets built.

Who owns the IP?

You do. You own all the IP and code AE Studio produces for you.

Your company already knows the answer.

Somewhere in your Slack threads, meeting recordings, and tickets, the answer to this week's hardest question already exists. The AI readiness assessment finds the two or three sources behind it, tells you whether your case is a build or a subscription, and hands you a ranked list of what to build first. About 3 weeks, and you keep everything it produces.

Our delivery leads each got back 15 hours a week. Yours are still spending them.

Start with an AI readiness assessment Talk to an engineer