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PJ (Prakshal Jain)
PJ (Prakshal Jain)

Posted on Originally published at privatesuperintelligence.si

Mapping a VC firm's AI stack by data flow: connectors, MCP and training defaults

#privacy #ai #fintech #security

Disclosure: I co-founded Mitosis Labs, which runs Private SuperIntelligence. This is an adaptation of the original guide.

If you are the person at a venture firm who wires up the tools, "which AI should we use?" is really a data-flow question. Each tool reads some slice of founder and LP data, through some connector, under some training default. Draw that for each candidate before comparing features.

Everything I say about vendors below comes from their own pages, accessed 2026-10-15. Sources are at the end.

The data-flow view

Group Tools What the tool reads Training default the vendor states
General assistants ChatGPT Business/Enterprise, Claude for Financial Services, Microsoft Copilot What users paste, upload or connect; for Copilot, Microsoft Graph content the user can already access Each says business data is not used for training by default (Microsoft: not used to train foundation LLMs)
Sourcing and relationships Harmonic, Affinity Vendor's company database plus what you sync; for Affinity, your pipeline, meetings and email Not covered in the original guide; ask
Documents and diligence Hebbia, V7 Go The documents and data you load Hebbia: never used to train its or providers' models. V7: "No training on your data"
Portfolio and LP reporting Visible, Standard Metrics Portfolio data, founder updates and documents Not covered in the original guide; ask

Connectors are where the scope expands

Three details matter more than the feature lists.

Inbox and calendar sync. Harmonic offers network syncing from inboxes, calendars and LinkedIn. Affinity's agents "prep your meetings, capture conversations, and write updates back to your pipeline." Once a tool syncs mail, it reads relationship data, not just company data. Affinity's security page lists SOC 2 Type II and ISO 27001 and encryption at rest and in transit, but did not cover model training or which model providers process data, so put that question in writing.

MCP servers. Visible connects AI workflows through MCP and Standard Metrics ships an MCP server for third-party LLMs. That is convenient, and it means portfolio data can flow into whatever model the user connects. Your data boundary becomes the union of both vendors' terms.

Permission inheritance. Microsoft says Copilot works over Graph content "that you have permission to access." Copilot's reach is your SharePoint and Teams ACLs. Fix oversharing before rollout. Microsoft also notes that models provided by Anthropic as a subprocessor are currently excluded from the EU Data Boundary.

Certifications as stated

  • OpenAI: SOC 2 Type 2, AES-256 at rest; Enterprise admins control retention, deleted conversations removed within 30 days unless law requires otherwise.
  • Harmonic: ISO 27001, SOC 2 Type II.
  • Hebbia: SOC 2 Type 2, ISO 27001:2022, ISO/IEC 42001:2023, US and EU regional processing, dedicated tenant "if needed".
  • V7 Go: "Encrypted end-to-end", access controls, audit logs.
  • Standard Metrics: "We are SOC 2 and GDPR certified."

A five-line vendor checklist

  1. Does it train on our data, and does the answer cover the model providers it uses?
  2. How long does it keep documents, prompts and outputs, and who on its staff can read them?
  3. Does every figure it produces cite a source document?
  4. Can it act outside the firm (email, CRM writes, sharing), and can we require approval?
  5. Can we describe it, function by function, in an LP's DDQ?

Visible's AI Sentiment Report found tool overload (49%) almost as common a blocker as security concerns (51%), so the checklist is also a filter for fewer tools.

Where Private SuperIntelligence fits

Private SuperIntelligence is an AI concierge that works across a firm's own email, documents and data, answers with citations and acts within permissions the firm sets. Each deployment is built for one client, from the hardware to the choice of model provider to where the data is stored. It is not a CRM or startup database and runs beside them.

Private SuperIntelligence takes a limited number of families at a time so every one gets the same standard of service. Book a private call (ref BVC1-DEV) to talk through your office with Alex Morris.

Prakshal Jain (PJ), Co-founder and CTO, Private SuperIntelligence (by Mitosis Labs)

Alexander Morris, Co-founder and CEO, Private SuperIntelligence (by Mitosis Labs)

Originally published at privatesuperintelligence.si. Vendor pages accessed 2026-10-15.

Sources

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