Wealth & Advisory AI
A

Addepar

Addepar is a New York headquartered data and portfolio intelligence platform for investment professionals, founded in 2009 and serving more than 1,400 firms across nearly 60 countries who manage and advise on close to $9 trillion of assets, of which over 40 percent sits in alternatives. Buyers span registered investment advisers, multi family offices, single family offices, private banks, institutions, asset owners, allocators and fund managers, with named clients including Morgan Stanley, AllianceBernstein and the Geneva multi family office Lobnek Wealth Management.

The platform unifies multi custodial data, illiquid alternatives and complex legal entity structures into a single portfolio view, and layers analysis, reporting, financial planning, projection through Navigator, and a trading capability launched in late 2024 that replaced the rebalancing technology acquired with AdvisorPeak. The open platform integrates with roughly 650 software, data and consulting partners. Offices run through New York, Salt Lake City, London, Edinburgh, Geneva, Dubai, Pune and Sao Paulo, with about 250 staff across Europe and the Middle East, against annual research spending stated at over $150 million. The AI line has three shipped parts.

Addison, launched in March 2026 and available to firms that opt in, is a native experience embedded in the platform that answers natural language questions about performance drivers, exposures and liquidity, understands portfolio structure, alternatives complexity and firm specific entitlements, and returns outputs the company describes as permission aware and traceable, tied directly to the underlying records. Alts Data Management applies machine learning with human verification to extract and normalize private markets data. Intelligent Statements converts unstructured financial statements into review ready files.

The company states that Addison originated in research aimed at building a proprietary large language model trained on its own accumulated historical data, and it acquired the workflow automation startup Arcus in May 2025 and folded that capability in. Announced next steps are proactive insight delivery with market aware context and cited sources, plus agentic workflows across data operations, analytics, forecasting and reporting.

Last VerifiedAugust 21, 2026
Compare Addepar with other vendors
Founded
2009
Headquarters
New York, New York, United States
Website
addepar.com
Categories
wealth-and-advisory, capital-markets-ai
Assessment

Capability Axes

Capability grades

15 of 15 axes rated · 5 graded A or B

AI Capability
AI Centrality
CC on AI CentralityArtificial intelligence is present but peripheral: a feature layer on a product whose value stands without it.
Vendor Published

The asset underneath is fifteen years of multi custodial aggregation, entity modeling, reconciliation, reporting and trading, even though the company now calls itself a data and AI platform. All of that stays intact without the models, and it is still the reason firms buy. Public and private markets differ.

The public markets side keeps working without inference, while the alternatives side degrades, since private markets data reaches the platform through machine extraction of unstructured statements. The result is mixed.

Autonomy and Oversight Model
BB on Autonomy and Oversight ModelA written commitment that the models work alongside human judgment, with real review surfaces, short of the full control structure: commonly the threshold at which the system stops or what happens after it is wrong.
Vendor Published

Three real controls are stated consistently across the vendor's own material rather than in one press release. Access is permission aware and entitlement aware, so the assistant sees only what the querying user may see, and firm specific entitlements are honored. Outputs are traceable and tied directly to the underlying records, so an adviser can follow any answer back to the source rather than accepting it.

The capability is opt in at firm level, so it is off until a firm turns it on, which is a real deployment control. Three limits remain. The shipped product analyzes rather than acts, so no gate has yet had to be described. The announced agentic workflows are said to keep humans in the loop, but that claim names no gate, no threshold and no escalation path. And there is no confidence surfacing beside the provenance.

Model Risk Management and Transparency
BB on Model Risk Management and TransparencyReal transparency mechanisms are published, such as per alert explainability, confidence scoring or split testing, without the validation package or supervisory mapping behind them.
Vendor Published

One property carries this, and it is a real one rather than a value statement. Every response is stated to be traceable and tied directly to the underlying records, so an output can be followed back to the portfolio data that produced it. That is checkable in a demonstration, which sets it apart from a vendor asserting explainability as a noun. Nothing else is published.

There is no accuracy or error rate, validation approach or benchmark, and no monitoring regime or drift policy, for a system answering questions about performance, exposure and liquidity that advisers will repeat to clients. The announced citation of sources is still a roadmap item.

Operational and Outcome Evidence
AA on Operational and Outcome EvidenceNamed customers with hard performance figures and enough method to test them.
Vendor Published

A named customer and a quantified outcome are joined rather than published in separate places. A client case study from a Geneva based multi family office reports roughly an 80 percent reduction in manual workload after moving onto the platform. Beyond that the installed base is named at the top end, with a global wire house and a major asset manager among the clients. The scale figures are specific and consistent across sources at 1,400 firms, nearly 60 countries and close to $9 trillion. The case study is published by the vendor, and the figure is the customer's reported experience rather than an independently audited measurement.

AI Safety and Data Stewardship
CC on AI Safety and Data StewardshipGeneral assurances that do not answer the question this axis asks, which is whether one customer’s data trains models serving its competitors. Unbounded cross client learning stated with no boundary grades here too.
Vendor Published

Addepar states affirmatively that its assistant originated in research aimed at building a proprietary large language model trained on its own accumulated historical data, and then publishes nothing further. Vendors usually either say nothing about training or assert that client data is never used for it. The word carrying the weight is securely, which describes a method and answers none of the questions that follow.

Nothing says what that accumulated data comprises or whether it is client derived. Nothing says whether the firms whose portfolios constitute it agreed to that use, whether anything is isolated between clients, or whether a firm can decline while still using the platform. Opt in is published, but it governs use of the assistant rather than contribution to what trained it, and conflating the two would be an error. The disclosure is more candid than the norm and leaves a buyer worse informed than a plain denial would.

Regulatory and Compliance
GLBA and Data Privacy Posture
CC on GLBA and Data Privacy PostureA standard privacy policy that covers the website rather than the service, or silence on a product that touches limited consumer data.
Vendor Published

A permissioned data model with granular role based access control is published, and encryption in transit and at rest is stated. The disclosure stops there. There is no privacy framework compliance statement, no processing addendum, no subprocessor list and no retention or deletion terms. That gap matters for a platform holding the complete balance sheets, entity structures and beneficial ownership of ultra high net worth households across nearly 60 jurisdictions.

Security Certifications and Trust Center
CC on Security Certifications and Trust CenterA single footer line, or certifications asserted without being enumerated, which is weaker than naming them because it invites an assumption a buyer cannot check.
Vendor Published

The vendor's own page says the platform aligns with industry frameworks such as SOC 2 Type II. That sentence borrows the authority of a named standard without claiming to hold anything. Aligning with is not holding, and "such as" makes even the list illustrative rather than complete. A buyer learns neither whether a report exists, nor its type, scope or period.

Real controls are stated alongside it: encryption in transit and at rest, and a permissioned model with granular role based access. A platform with a global wire house as a client has passed that firm's vendor review and almost certainly holds current reports, none of which are public.

Regulatory Status and Licensure
CC on Regulatory Status and LicensureThe regulatory position is unstated. Most vendors in this index are technology suppliers and being unlicensed is the correct posture, so this grade records silence about the posture, not a missing license.
Vendor Published

There is no license, no supervised test of the product and no program enrollment. The trading capability brought in house in late 2024 is the one place where registered status might attach, and nothing published addresses it. That remains an open question.

AI Governance and Bias Disclosure
CC on AI Governance and Bias DisclosureResponsible artificial intelligence committed to in policy language with no evaluation behind it, on a product whose bias surface is modest.
Vendor Published

Nothing is published on fairness testing, performance variation or governance of outputs. Consumer protection exposure is low, since this is portfolio analytics and reporting for professionals managing the assets of wealthy households, not a decision about an individual's access to a financial service. The residual concern is narrower. An assistant that surfaces what matters most across a book of business is prioritizing which clients and which holdings get attention, and in a wealth business attention is the service being sold.

AI Liability and Recourse
CC on AI Liability and RecourseMechanisms that enable challenge, such as audit trails and source traceability, with nothing standing behind the output and no route for the person affected.
Vendor Published

No allocation of responsibility for a wrong output is published, and there is no route for any affected party, who in this case is the underlying household rather than the paying firm. The exposure is indirect but not trivial. An assistant answering questions on exposure and liquidity feeds analysis that reaches a client. Traceability helps an adviser check an answer, but it gives no one a remedy when the answer was wrong and acted upon.

Integration and Deployment
Model Supply Chain Disclosure
CC on Model Supply Chain DisclosureThe architecture is described and no provider is named.
Vendor Published

The company states the model is proprietary and trained on its own data. That tells a buyer the provenance is internal rather than a third party interface call, which is fractionally more than the usual bare claim of proprietary technology. Below that top line there is nothing. No base model, architecture, version, hosting arrangement or supplier is named for a system the vendor describes as a large language model, and in practice such models are very rarely built from nothing.

Core Systems and Integration Depth
AA on Core Systems and Integration DepthNamed integrations with the systems of record, core banking, policy administration, custodial or contact center platforms, verifiable in marketplace listings or public API documentation.
Vendor Published

Integration depth runs by function and by counterparty. The platform is the aggregation layer itself, pulling multi custodial feeds, illiquid alternatives and complex legal entity structures into one reconciled view, which makes it the operational core for the firms that run on it rather than an adjacent tool. On top of that sits an open integration estate stated at roughly 650 software, data and consulting partners. Specific named integrations are published, including a financial planning tool that builds plans from live Addepar holdings. A trading capability was brought in house in late 2024.

Deployment Model and Data Residency
CC on Deployment Model and Data ResidencyCloud only with nothing stated, which is the category norm.
Vendor Published

Nothing published on hosting, region, tenancy or residency. The gap is more consequential here than for a domestic vendor, because this platform holds portfolio and beneficial ownership data for firms in nearly 60 countries, including European and Swiss private banking clients operating under bank secrecy and data protection regimes where residency is a routine procurement question. Eight offices across four continents is a corporate footprint, not a data residency statement, and the two should not be confused.

Commercial
Commercial Transparency
CC on Commercial TransparencyNo price is published and engagement runs through a demo form, which is the norm in this index.
Vendor Published

No price, tier, unit or pricing basis is published anywhere. An independent research profile characterizes the platform as more expensive than its competitors. That is third party commentary, and it is the only pricing signal that exists in public.

Institution and Segment Coverage
AA on Institution and Segment CoverageThe financial segments served are named and each carries its own maintained material, whether the coverage is broad or deliberately narrow.
Vendor Published

More than 1,400 firms in nearly 60 countries have close to $9 trillion managed or advised on the platform. The buyer types are distinct rather than restatements of one another. They include registered investment advisers, multi family offices and single family offices, along with private banks, institutions and asset owners, and allocators and fund managers. They range from boutiques to a global wire house. Asset coverage spans public and private markets, with over 40 percent of platform assets in alternatives, which is the hard half. There are eight offices across four continents.

Tracked Since Listing

Product updates

Material product, regulatory, evidence and commercial changes at Addepar, each verified against a live source and tagged to the capability axis it bears on. Funding rounds and awards are not product changes and are not logged.

Sep 14, 2026Integration / interoperabilityPartially verified

Addepar is one of the connectors in Claude for Financial Advisors, which Anthropic launched on 14 September. Advisors can give Claude governed access to Addepar portfolio data and analytics across public and private markets for research, meeting preparation and follow up.

Bears on: Core Systems and Integration DepthSource
Our read on this update →Tracked since Sep 2026

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The index publishes no overall score or ranking. See what we assess and the methodology.

Commercial

Pricing

Vendor-published figures are labeled as such. Figures labeled “Estimated” are derived from third-party sources and have not been confirmed by the vendor.

No pricing data has been verified for this vendor. Pricing information will be published here once confirmed through vendor disclosure or third-party estimation.

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AI FinTech Index

The AI FinTech Index is an independent index that tracks changes to AI vendors in financial services. It holds 610 vendors across banking, lending, insurance, wealth, capital markets and financial crime compliance, each graded on the same 15 capability axes from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
October 20, 2026
The AI FinTech Index is an editorial reference, not a regulatory body. Vendor data is verified against published sources and public regulatory filings. Figures labeled “Estimated” have not been confirmed by the vendor. See the Methodology page for evaluation standards and limitations.
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