Wealth & Advisory AI
A

Ammonite AI

Ammonite AI is a United Kingdom company selling Planbot, a report drafting tool for financial advice firms, launched in February 2026. Its co founders Rob Harradine, who is also chief commercial officer, and Caroline Duff are both former Chartered financial advisers with around thirty years of combined experience in wealth management, and previously built and sold their own advice business, with Duff also working as a paraplanner.

Planbot converts an advice firm's existing manually populated templates into model driven documents, ingesting fact finds, meeting transcripts, pension policy documents, portfolio valuations, statements and fee schedules and populating the firm's own template in seconds. It is aimed specifically at suitability reports and annual reviews, the two documents that create the largest drafting backlog in a paraplanning team. The firm keeps control of the template and can change it on an ongoing basis without vendor involvement, and exported documents retain the firm's own layout, tone, voice and branding.

The company reports that users have more than halved the time taken to produce a suitability report. Simpson Wood, an advice firm using the tool to clear an annual review backlog, is named publicly with its head of client servicing describing faster turnaround to clients. The founders position the product explicitly as assistive rather than autonomous, stating publicly that the model can make mistakes and that a human check is required at the end of the process to confirm the output remains compliant and suitable.

Last VerifiedAugust 19, 2026
Compare Ammonite AI with other vendors
Founded
Headquarters
United Kingdom
Website
ammonite-ai.com
Categories
wealth-and-advisory, compliance-and-surveillance
Assessment

Capability Axes

Capability grades

15 of 15 axes rated · 4 graded A or B

AI Capability
AI Centrality
AA on AI CentralityThe artificial intelligence is the product. Remove the models and there is nothing left to sell.
Vendor Published

The product is a generation engine and nothing else. Planbot ingests fact finds, meeting transcripts, policy documents, valuations and fee schedules and writes the firm's own template from that unstructured material. Remove the models and what remains is the blank template the firm already had, which is the starting position the product exists to improve on.

There is no workflow engine, no record system and no rules layer underneath to fall back on, which makes this the cleanest possible pass of the removal test and places it with the other generative drafting tools in this pocket rather than with the platforms.

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

The positioning is the most candid in this pocket and it is doing real work. A co founder states publicly in trade press that the model can make mistakes and that a human check is therefore required at the end of the process to confirm the output remains compliant and suitable, and the founders repeatedly frame advisers and paraplanners as remaining firmly in charge of the report writing process.

Design supports the claim: the firm owns and edits the template, changes it without vendor involvement, and receives a draft to review and export rather than anything sent onward. It stops short of the top grade because none of this is a mechanism. No checkpoint is enforced in the product, no confidence indication accompanies generated passages, nothing marks which content was drawn from which source document, and no record evidences that a review took place.

Model Risk Management and Transparency
CC on Model Risk Management and TransparencyTransparency is claimed in general terms with no mechanism a model validator could interrogate.
Vendor Published

There is an unusual and creditable honesty here that stops short of measurement. A co founder states in trade press that the model can make mistakes, which is more than any other vendor in this pocket concedes publicly, and marketing separately describes the output as having impressive consistency and accuracy. Neither position is quantified.

No error rate is published for template population or extraction, no evaluation methodology, test set or independent assessment exists, and nothing describes how often a generated report requires substantive correction rather than editing. Acknowledging that a model errs without publishing how often it errs leaves a firm no better able to size the review burden it is taking on.

Operational and Outcome Evidence
BB on Operational and Outcome EvidenceVendor aggregate claims with real figures, or audited scale disclosures from a publicly listed company.
Vendor Published

For a product launched in February 2026 the evidence is better than the age would suggest. One customer firm is named publicly, Simpson Wood, with its head of client servicing quoted by name describing faster turnaround and progress through an annual review backlog. The company states users have more than halved the time taken to produce a suitability report.

Coverage is genuinely independent, running across four separate United Kingdom advice trade publications rather than the vendor's own channels, and the founders' background as former Chartered advisers who built and sold an advice business is externally verifiable.

What holds it below the top grade is that no figure is attached to the named customer, whose quotation is qualitative, the halving claim is vendor stated across unnamed users, and a founder's suggestion that the tool could triple adviser capacity is speculation rather than a measured result.

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

Neither half is addressed publicly. Nothing states whether uploaded fact finds, meeting transcripts, valuations and policy documents are used to train or improve models, whether any third party provider is permitted to train on that material, whether a firm can decline such use, or how long uploaded material and generated drafts are retained. Two direct competitors in this same pocket publish an explicit position on exactly that question.

On the safety side, no control against fabricated content is described for a document that becomes regulatory evidence, no evaluation of output quality is offered, and nothing sets out what the system does when the uploaded material is incomplete or internally contradictory.

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

Nothing substantive on privacy was located for a product that receives complete client files by upload. No privacy management certification is held, no retention or deletion period is published for uploaded documents, transcripts or generated drafts, and no position is stated on the lawful basis for processing, on data subject rights over material supplied by the adviser rather than the client, or on how a client would learn their file had been processed by a third party system. For a tool whose inputs include pension policy documents and full financial circumstances, this is the least documented area of the record.

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

No information security management certification, service organisation control attestation, trust centre, security page or scope statement was located. The material a firm uploads is among the most sensitive it holds, comprising complete fact finds, pension policy documents, portfolio valuations and fee schedules for named retail clients, and the file upload model means that material is transferred to the vendor by design rather than accessed in place. Advice firms are routinely asked by their networks and compliance oversight providers to evidence supplier security, and nothing published here would answer such a request.

Regulatory Status and Licensure
BB on Regulatory Status and LicensureThe regulatory position is clearly stated and appropriate to the product, with part of the verification left to the buyer.
Vendor Published

Ammonite holds no financial licence and no regulator has assessed the product, which is the expected posture for a supplier. The regulatory grounding comes from the artefact it produces: suitability reports and annual reviews are the mandated file level record that a recommendation was appropriate for a client, and the tool is built around those documents specifically rather than around generic productivity.

The founders' background as former Chartered advisers who ran a regulated advice business gives the product design direct practitioner grounding in the relevant conduct rules. It stops short of the top grade because no authorisation, registration, programme participation or regulator engagement exists, and no external party has assessed whether outputs meet the standard the documents are held to.

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 published addresses whether the system performs evenly across the clients whose files it processes. The product ingests meeting transcripts alongside documents, which carries the transcription variation problem common to this pocket, and it also generates the narrative rationale explaining why a recommendation suits a particular person, so uneven handling of how different clients describe their circumstances would surface directly in the regulated record. No demographic analysis, no bias testing methodology, no evaluation across client or speaker populations and no governance framework covering model fairness was located.

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

The founders are clear that responsibility for the final document rests with the adviser or paraplanner, which is the correct regulatory position and is stated more plainly than most peers manage. It resolves the vendor's exposure rather than establishing anyone's remedy.

No accuracy guarantee, remediation commitment or allocation of liability between vendor and firm was located, and no route exists for the retail client, whose fact find and policy documents were processed and whose suitability rationale was drafted by a model, to learn that this occurred or to establish how their circumstances were interpreted if the advice is later disputed.

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

No base model, provider, version or component is named for document ingestion, extraction or template population, and no subprocessor list is published. The company describes combining adviser and paraplanner experience with cutting edge technology, which characterises the team rather than the stack, and leaves open whether the underlying models are its own or licensed from a third party.

No identifier exists that a firm could record against a generated suitability report to establish later which system produced it, which matters for a document that may need to be defended years after it was written.

Core Systems and Integration Depth
CC on Core Systems and Integration DepthIntegration claimed through standards or connectors with no system named and nothing to verify.
Vendor Published

The product deliberately sits outside the firm's systems rather than inside them, operating on a file upload workflow where documents and transcripts are supplied to it and finished drafts are exported back. No back office, planning or record system integration was located, no meeting capture is offered so transcripts must come from elsewhere, and a competitor's published comparison advises firms to verify meeting capture and back office connectivity directly with the vendor, which points the same way.

The founders present this as a deliberate choice, describing the product as built to work the way advice firms already operate rather than requiring them to adopt a technology company's workflow. That is a coherent position and it still leaves the integration depth at the bottom of this pocket.

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

Delivery is a hosted service reached by uploading documents and downloading drafts. No hosting region or country is named, no in country residency option is described, no data transfer mechanism is set out and no subprocessor list exists.

The gap matters because the upload architecture moves client files to the vendor's environment as a matter of course rather than as an exception, so where that environment sits is a first order question for any firm conducting due diligence, and a competitor of comparable size in this same pocket publishes the processing country for each of its providers.

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 rates, tiers, seat pricing, volume bands, minimum terms or trial arrangements were located. For a tool sold to advice practices ranging from single adviser firms to larger groups, the pricing unit itself is unclear, with no indication whether the charge is per user, per report or per firm. Every route resolves to a demo or contact request. Two direct competitors in this pocket publish either a per user monthly rate or a public pricing page, so the absence reflects a choice rather than a norm in this segment.

Institution and Segment Coverage
CC on Institution and Segment CoverageSegments claimed broadly, banks, fintechs, credit unions, without evidence any of them has its own maintained surface.
Vendor Published

Coverage is narrow in both senses that matter. The product serves one jurisdiction and one buyer type, United Kingdom financial advice firms, and within that it addresses one function, the drafting of suitability reports and annual reviews for advisers and paraplanners. The tool launched in February 2026 and one customer firm is named, so market presence is early rather than established. There is no deployment outside the United Kingdom, no adjacent institution type, and the document formats and regulatory expectations are built around a single national rulebook.

Alternatives to Ammonite AI

The closest documented capability profiles to Ammonite AI in the same categories, ordered by similarity across the same fifteen axes the index grades every vendor on. Closest documented profile, not a claim that either product does the same job. No vendor pays for placement.

Documents Core Systems and Integration Depth where Ammonite AI does not

Documents Core Systems and Integration Depth where Ammonite AI does not

Documents AI Governance and Bias Disclosure where Ammonite AI does not

Documents Core Systems and Integration Depth and Model Supply Chain Disclosure where Ammonite AI does not

Documents Institution and Segment Coverage and Core Systems and Integration Depth where Ammonite AI does not

Documents Institution and Segment Coverage where Ammonite AI does not

Similarity is computed axis by axis from published grades, not from a composite score. The index does not aggregate grades into a total. See the fifteen axes 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.

Contact us

Found a vendor we missed? Have feedback on the index? We’d love to hear from you.

AI FinTech Index

The AI FinTech Index is an independent index that tracks changes to AI vendors in financial services. It holds 489 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
September 5, 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.
© 2026 AI FinTech Index
3801 N Capital of Texas Hwy, Ste E240 · Austin, TX 78746