Introducing SecureLend Tag: @SecureLend for Finance Teams

SecureLend Tag is a new way for finance teams to underwrite. Tag @SecureLend where your team already works, and it qualifies, gathers, verifies, analyzes, scores, and drafts decision-ready underwriting and investment memos — running on the AI model you choose, connected to the data sources you own.

Underwriting has always been a team sport — analysts, associates, and partners passing files, spreadsheets, and memos back and forth. SecureLend Tag brings an AI underwriter directly into that flow. Instead of switching tools, you simply tag @SecureLend on a deal, a company, or a document, and it does the work in stages you can watch and check.

Tag the underwriter into your workflow

You ask in plain language — “@SecureLend screen this deck,” “@SecureLend draft the credit memo,” “@SecureLend verify these financials.” SecureLend breaks the request into stages — qualify, gather, verify, analyze, score, draft — and runs them in sequence, showing its work and its sources at each step. The output is a decision-ready record, not a black-box answer.

One SecureLend for the whole deal team

Within a deal channel or workspace, there is one SecureLend that everyone shares. It builds context as the deal progresses, so the team stops re-explaining the thesis, the structure, and the prior analysis. Everyone works from the same underwriting record.

Model-agnostic by design

SecureLend Tag is not tied to any single AI provider. You choose the model behind each step — a frontier model for memo synthesis, a cheaper model for document classification — and you can change it as the frontier moves. No model lock-in, no dependency on one vendor's roadmap, pricing, or outage. Every decision records its model lineage, so each memo is reproducible and auditable.

Bring your own data, skills, and API keys

SecureLend Tag connects to the tools and data you already run. You bring:

• Your data sources — data rooms, CRMs, filings, bank statements, portfolio systems — connected over MCP and your own connectors.

• Your skills — your underwriting policies, rubrics, and memo templates, so the output matches how your firm actually decides.

• Your API keys — your model and data-provider credentials, used in your tenant. You bring the keys; you keep the control.

You keep owning your data

This is the part that matters most for finance teams. SecureLend never takes ownership of your data. Your sources stay in your systems and your tenant; SecureLend reads what you connect, produces attributed outputs, and writes the audit trail and model lineage into your environment — not a vendor black box. Nothing is used to train shared models. You connect your data, and you keep owning it.

What you can tag it for

• Deal & pitch screening — “@SecureLend screen this deck against our thesis.”

• Underwriting & credit memos — “@SecureLend draft the underwriting memo.”

• Investment / IC memos — “@SecureLend prepare the IC memo outline.”

• Document & financial verification — “@SecureLend verify these statements.”

• Diligence prep — “@SecureLend build the diligence checklist.”

Is there a “Claude Tag” for finance or underwriting?

General-purpose team assistants like Claude Tag popularized a powerful pattern: tag an AI teammate in the tools you already use and let it do real work. SecureLend Tag is that pattern, purpose-built for finance — the Claude Tag for finance, underwriting, and financial analysts. The difference is the domain and the guarantees: SecureLend runs your underwriting policies and rubrics, produces attributed, decision-ready memos, and — critically for finance teams — is model-agnostic and keeps your data sources under your ownership. You bring your own data, skills, and API keys; SecureLend brings the underwriting.

For a financial analyst, that means tagging @SecureLend to spread statements, build a comparable set, or draft a credit or investment memo — with every figure traceable to a source you control, on the model you choose.

Getting started

SecureLend Tag is available for lending, VC, PE, private credit, insurance, and investment-banking teams. Connect your data sources and model keys, point it at your underwriting policies, and tag @SecureLend on your first deal.

Frequently asked questions

Is SecureLend Tag like Claude Tag, but for finance?

Yes. SecureLend Tag applies the tag-an-AI-teammate pattern specifically to underwriting and financial analysis, adding the model-agnostic and data-ownership guarantees finance teams require.

Which AI model does SecureLend Tag use?

Whichever you choose. SecureLend is model-agnostic — you select the model per step and can change it at any time.

Does SecureLend store or train on our data?

No. Your data stays in your tenant and systems, SecureLend reads only what you connect, and nothing is used to train shared models. You keep owning your data.

How is this different from a generic AI assistant?

SecureLend Tag is purpose-built for underwriting: it runs your policies and rubrics, produces attributed, decision-ready memos, and records model lineage and an audit trail — not a one-off chat answer.