Port of Context for Private Equity
Agents need to understand your firm’s data before they can use it.
Port of Context specializes in agent execution infrastructure for private equity firms. We build the layer that lets agents run safely and traceably on decades of sensitive data. That takes engineering, not vibe-coding.
Your ontology[ meaning ]
How your data categories relate, so that agents can grasp them exactly the way your firm does.
Your taxonomy[ structure ]
How your firm categorizes its data, in its own terms.
Your deep data[ source ]
Decades of your firm’s most sensitive records, down to every email, memo, and deal.
A $7B private equity fund runs 50+ custom agents on Port of Context.
deal-sourcing · diligence · portfolio monitoring
Live at Prudential Financial and Block.
Network intelligence
Find the warm path to anyone, in one prompt.
Every partner and employee brings in thousands of contacts over years spent at your firm. Port of Context engineers agents that map all of them, so deal sourcing starts from a warm path.
Portfolio monitoring
Monitor portcos without drowning in spreadsheets.
Every portfolio company’s numbers sit across dozens of spreadsheets and shared drives. Port of Context engineers agents that monitor all of them.
Data rooms
Every data room you’ve ever built, cleaned up, sorted, and queryable.
Spreadsheets, decks, contracts and memos, scattered across years of M&A deals and due diligence. Port of Context reads every file in every VDR and sorts it into one structured index your team can query.
Put stress-tested agents on top of the tools you already use.
Don’t force new workflows and UI onto your team. Run agents on the tools your team is already used to.
How it works
Engineers build the foundation. Your team builds on top.
Resilient agents come from disciplined foundations.
- 1
Clean the data at its source
We index all of your deep data so that it can be accessed by agents with proper controls and tooling.
- 2
Build a custom MCP server over it
We tune the server the exact way agents need to read and query it.
- 3
Eval rigorously
We build evaluation cases on your actual workflows and keep refining them, so each agent proves it executes properly before it ever reaches production.
- 4
Your firm builds agents in one prompt
With the MCP server in place, your own team can now reliably build production-grade agents on top.
Map Port of Context to your environment.
We'll look at your infrastructure, models, and compliance constraints, then tell you honestly whether Port of Context fits. A real engineer follows up fast.
FAQs
- What is the difference between an ontology and a taxonomy?
- A taxonomy is how a firm categorizes its data in its own terms. It tells an agent where things belong. An ontology defines how those categories relate to each other and encodes the specific logic the firm uses to put its data to work. An agent needs both. The taxonomy tells it where to look, and the ontology tells it what the data means once it gets there.
- What is agent execution infrastructure?
- Agent execution infrastructure is the layer that lets AI agents run on a firm’s systems and data in production. It covers how agents read and query the data, which tools they can call, how their access is controlled, and how every run is traced back to its sources. Port of Context builds this layer for regulated firms on top of the tools they already use.
- How do AI agents handle due diligence and data room documents?
- Badly, unless the data is prepared first. A data room arrives as thousands of PDFs, spreadsheets, emails, and call notes with no shared structure, and an agent pointed at that raw pile will miss things. The reliable approach is to index the material at its source, build a custom MCP server over it, and give agents controlled, queryable access. Every answer then traces back to the underlying document, so your team can verify what the agent found before it reaches an IC memo.
- Is Port of Context a virtual data room (VDR)?
- No. A virtual data room stores and shares deal documents during a transaction. Port of Context reads the data room contents your firm already holds, from the rooms it runs to the archives and exports of past deals, along with shared drives and inboxes. It indexes all of it at the source and gives agents controlled, queryable access. Your firm keeps its existing VDR and uses Port of Context to put decades of its contents to work.
- Are we locked into one AI model or vendor?
- No. The infrastructure is model-agnostic. Agents run on Claude, GPT, Gemini, or open-weight models, and the firm can switch when a provider changes pricing, degrades, or gets ruled out by policy. The data layer, the MCP server, and the ontology work stay yours, so a model change never means rebuilding the foundation.
- Do we need to replace the tools our team already uses?
- No. We build on top of the tools your firm already runs, including Excel, Outlook, SharePoint, Salesforce, and Bloomberg. Agents reach those systems through the MCP server, with access controls in place. Your team keeps working where it already works, and the agents operate on the same data.
- What does it take for our own team to build an agent?
- A prompt, once the foundation is in place. The engineering happens up front, in cleaning the data at its source, building the MCP server, and writing evaluation cases against your actual workflows. After that, someone on your team describes the agent they need and it runs on infrastructure that is already controlled and traceable.