Agentic AI for the parts of finance nobody wants to do by hand - and every answer comes with a citation.
Cape.ai's brand mark and tagline. The company rebranded from Cape Privacy on its shift into agentic AI for regulated finance.
Most enterprise AI pitches fall apart on a single question from the compliance desk: where did that answer come from? Cape.ai built its entire company around answering it.
Cape - legally Cape, Inc., and better known to the public by its web address, cape.ai - is a New York company building an agentic AI platform aimed squarely at financial services. Its software automates the document-heavy grind of the back office: enhanced due diligence, third-party risk reviews, the reading of SOC reports, KYC and anti-money-laundering onboarding, and the assembly of regulatory reports. In an industry where a wrong answer can trigger an audit, Cape's differentiator is not raw intelligence but accountability - every action the AI takes is cited, traceable and auditable, and the system can run inside the customer's own environment so sensitive data never has to leave.
That posture is not an accident. Cape started in 2018 under a different name, Cape Privacy, building an encrypted-learning platform that let organizations collaborate on machine-learning models without exposing the underlying data. The market moved, generative AI arrived, and the founders carried their hard-won lesson - regulated industries will not trust what they cannot verify - straight into a new product. The name on the door changed. The obsession with trust did not.
A large share of work inside a bank is, quietly, document processing. Cape.ai goes after exactly that.
Compliance and operations teams spend enormous hours reading unstructured documents - vendor SOC reports, due-diligence packets, onboarding files - then re-keying findings into systems. It is slow, expensive and error-prone.
Banks, asset and private-markets managers, and insurers whose operations, risk and compliance teams face heavy document volumes and cannot send sensitive data to a public chatbot.
AI agents that are adaptive and explainable, with full data lineage. Outputs are cited back to source, and the platform blends agentic reasoning with deterministic automation for repeatable tasks.
We founded Cape because we want to live in a world where we can have the benefits of technology without compromising privacy.
Automates business-process operations across structured and unstructured data. Agents are adaptive, explainable and governance-ready, with cited outputs, complete data lineage and on-premise or private-cloud deployment.
Positioned 2024Describe the process you want to automate - in plain English, by uploading a document, or even a video - and Cape auto-generates a draft agent and workflow to run it.
Positioned 2024Enhanced due diligence, third-party risk via SOC report analysis, KYC/AML onboarding, suspicious-activity (SAR) and currency-transaction (CTR) report analysis, and regulatory reporting.
Financial servicesThe original product: an encrypted-learning platform for secure collaboration on ML models with data kept encrypted throughout - later evolving into private-LLM and guardrail tooling before the pivot.
Since 2018Plenty of tools can summarize a document. Far fewer can prove where each line of the summary came from and run without the data ever leaving the building.
Cited by default. Every AI action is traceable to its source with full data lineage - the answer to the compliance desk's favorite question is built into the product.
Data stays home. Deployment on-premise or in a private cloud means data never leaves the customer's environment unless explicitly approved - a hard requirement for regulated buyers.
Agentic plus deterministic. For tasks that must run identically every time, Cape uses rules-based automation instead of letting a model improvise - a distinction that matters when a regulator is watching.
Domain-specific. Rather than a horizontal chatbot, Cape targets named financial workflows - EDD, TPRM, KYC/AML - where the value is concrete and measurable.
Both founders trace back to GoInstant, a Halifax startup Salesforce acquired in 2013.
25+ years leading teams in data, analytics and AI. Prior executive roles at HEAVY.ai, Neokami (acquired by Relayr/Munich Re), Cisco and Composite Software (acquired by Cisco).
20+ years as a technologist, entrepreneur and angel investor. Previously co-founded GoInstant, acquired by Salesforce in 2013.
Roughly $27M raised in total, anchored by a $20M Series A in 2021 - notable for a team that has stayed lean.
| Round | Amount | Date | Selected investors |
|---|---|---|---|
| Seed / early | ~$5M | 2019-2020 | boldstart ventures, Version One Ventures, Haystack, Radical Ventures |
| Series A | $20M | Apr 2021 | Evolution Equity Partners (lead), Tiger Global Management, Ridgeline Partners, Tom Noonan (Downing Lane), plus existing investors and Jevon MacDonald |
| Total | ~$27M | — | — |
Che Wijesinghe and Gavin Uhma launch the company in New York with a Halifax engineering base, focused on encrypted machine learning.
Secures support from boldstart ventures, Version One Ventures, Haystack and Radical Ventures.
Raises a Series A led by Evolution Equity Partners with Tiger Global and Ridgeline Partners, bringing total funding to roughly $27M.
Rebrands around cape.ai and launches an agentic AI platform and Cape Agents for financial-services business-process automation.
Positions as domain-specific AI for enhanced due diligence, third-party risk, KYC/AML and regulatory reporting with cited, auditable, on-premise deployment.
Cape.ai sits at the intersection of agentic AI and RegTech - the tooling financial firms use to keep pace with regulation. Its competition spans dedicated AML and third-party-risk vendors such as Vigilant AI, horizontal document-AI and enterprise LLM platforms, and the ever-present option of banks building in-house.
Its wager is that in regulated finance, the winning product is not the smartest-sounding one but the most defensible one. Business model is classic B2B enterprise SaaS - subscription access to the platform, historically with usage-based pricing tied to data processed - sold on a promise of large productivity gains and lower manual compliance cost.
Every AI action is fully cited and transparent - no black box behavior, and data never leaves your environment unless explicitly approved.
Cape.ai was originally Cape Privacy, focused on encrypted machine learning before the pivot to agentic AI.
It still tweets from @capeprivacy - a fossil of the former name.
The founding DNA traces to GoInstant, a Halifax startup Salesforce bought in 2013.
You can build an agent by uploading a video of a process and letting Cape reverse-engineer the workflow.
The logo is a stylized sun / cape mark rendered as an animated ring of rays.
A lean, ~17-person team betting that regulated finance will only adopt AI it can audit.
Cape.ai builds an agentic AI platform for financial-services firms that automates document-heavy operations - enhanced due diligence, third-party risk and SOC report analysis, KYC/AML onboarding and regulatory reporting - with cited, auditable outputs.
Yes. Cape (legally Cape, Inc.) started as Cape Privacy in 2018 focused on encrypted machine learning, then pivoted to agentic AI for financial services and now operates as Cape.ai.
It was co-founded in 2018 by Che Wijesinghe (CEO) and Gavin Uhma (CTO). Both trace roots to GoInstant, a Halifax startup acquired by Salesforce in 2013.
Roughly $27M in total, including a $20M Series A in 2021 led by Evolution Equity Partners with Tiger Global Management and other investors participating.
Cape deploys on-premise or in the customer's private cloud, so data does not leave the customer's environment unless explicitly approved, and every AI action is cited with full data lineage for auditability.
Compiled from public sources including Cape.ai, Crunchbase, Built In NYC, AlleyWatch and Entrevestor. Figures such as revenue and early-round amounts are third-party estimates and approximate. Last reviewed July 2026.