11x

There is no product without the models and the company has never had one. Founded in 2022 as an autonomous outbound company, every capability sold is inference: prospect research, message composition, reply interpretation and response, meeting booking, and telephone conversation in the voice product. Remove the model layer and nothing remains, not a diminished tool but an empty account, because the vendor does not sell a sequencer, a database or a dialer that a human would operate.

The commercial framing makes the same point from the other direction, since the product is priced against a salary rather than against software and is described as a worker rather than an application, which is a positioning only available to a company whose entire deliverable is model output. The announced re-platforming onto a newer agentic architecture is a rebuild of the model layer itself rather than a feature addition to something else.

This is the second record in this index to take the top band here and both are agent native companies founded after 2022, which is the vintage split behaving as the convention describes. Ask what a deployment produces before any configuration.

High autonomy across two channels, with controls that exist and that users report as laborious rather than sufficient. The outbound agent prospects, writes, sends, reads replies and books meetings without a person in the loop, and the voice agent conducts calls, so both operate unattended by design.

Real configuration controls are described in user accounts rather than vendor documentation: customers report building prompts, defining rules and maintaining blacklists of names and domains, which confirms that suppression and constraint mechanisms exist and are operator managed.

The revealing detail is what users say they had to blacklist, namely their own existing customers, which indicates the agent will contact anyone in scope unless explicitly excluded rather than defaulting to a bounded target set. That is an oversight model placing the entire burden of exclusion on the operator, and multiple accounts describe the effort as extensive without producing acceptable output.

Nothing published describes approval gates, volume ceilings, or a stop control for work in flight. Ask what the agent will contact by default, what must be excluded manually, and whether outreach can be held for review before sending.

An entirely model driven product with nothing published about the models. No provider, family or version is named, no model card exists, and no accuracy, quality or evaluation figure appears for research, message generation, reply interpretation or voice conversation.

The company publicly announced a full re-platforming of its outbound agent onto a newer agentic architecture, with the incoming chief executive citing substantial product improvements, and that announcement carries no technical detail, no comparison against the prior version and no published measurement, so a buyer cannot establish what changed or whether it addressed the personalisation complaints that prompted it. That gap is the consequential one here.

Where user communities report output quality as the core failure, an evaluation figure is the only thing that could distinguish a genuine rebuild from a repositioning, and none is offered. Ask which models power research, generation and voice, what evaluation covers output before it reaches a prospect, and what measured improvement the re-platforming delivered against the prior version.

The published evidence base has been contested by the parties named in it and has not been replaced with verifiable substitutes. This grade addresses the state of the evidence rather than the merits of any allegation, and the dispute is recorded rather than adjudicated.

A March 2025 investigation by a technology publication reported that companies displayed as customers disputed being customers, with one of them confirming publicly that its relationship had been a one month trial and the other denying a client relationship, and cited former employees on revenue recognition practices and on early churn running between seventy and eighty percent in the first three months. The chief executive at the time called the claims inaccurate.

That denial is on record and is not resolved here. What follows for this axis regardless of who is right is that a buyer verifying references against the published logo set encountered contradiction from the named companies themselves, and no replacement evidence with stated population, period or method has since been published.

Independent hands on testing does exist, with one reviewer running two hundred leads over two weeks, and it reports the same personalisation gap that user communities describe. Most other third party analysis is written by direct competitors and was weighted accordingly. Ask for three current customers you source independently rather than from a reference list, and for retention measured across a stated cohort.

Three regulated channels operated autonomously and no compliance apparatus published. The outbound agent sends email and social messages and the voice agent places telephone calls, which brings messaging law, platform rules and telephone preference regimes all into scope simultaneously.

Nothing published describes consent basis, suppression list handling, unsubscribe mechanics, preference register screening for the voice product, calling window enforcement, or what obligations the vendor considers to transfer to the customer.

The one mechanism evidenced is user reported rather than documented: customers describe maintaining their own blacklists of names and domains, which places suppression entirely in the operator's hands and, by the accounts given, requires them to exclude their own existing customers manually.

A product supplying a set number of contacts as part of the subscription is also supplying the target list, which makes the consent basis for contacting those individuals a direct question for the vendor rather than a downstream one. Ask what suppression the agents apply before contacting anyone, what preference register screening applies to the voice product, and the lawful basis for the supplied contacts.

No privacy documentation was reached on the routes taken this pass. No privacy policy contents, processing agreement, subprocessor list, transfer mechanism, retention period or data protection officer was located. This records what a buyer could establish before contacting sales rather than a finding of absence.

The corpus makes the questions substantial for a company of this size: the platform holds supplied contact records and research on individuals at prospect organisations who never contacted the customer, the full text of outbound correspondence, replies those individuals sent, and in the voice product recordings or transcripts of telephone conversations. All of that concerns people whose relationship is with neither the vendor nor its customer at the point of collection.

The company operates a European origin story and sells internationally, which raises transfer questions nothing addresses. Ask for the processing agreement, the subprocessor list, the retention period for prospect research, correspondence and call records, the transfer mechanism, and how a contacted individual would exercise rights over data held about them.

The subscription includes contact data and the source is not named. Third party reporting on the commercial terms states that a set number of contacts is included in the annual price, which means the vendor is supplying prospect records rather than only acting on a list the customer brings, and that makes provenance a direct question rather than a peripheral one.

Nothing published identifies the data provider, describes whether records are licensed or gathered, states a lawful basis for holding personal data on individuals who have no relationship with either party, or offers any indemnification position. The research capability compounds it, since the agent is described as researching prospects before writing to them, which implies gathering further information about named individuals from sources the vendor does not disclose.

For a product whose entire function is contacting people, the absence of any published account of where those people's details come from is the substantive gap on this axis. Ask which providers supply the included contacts, on what basis, what the research layer draws on, and whether provenance is indemnified.

Outreach runs across a professional social network and no method is described anywhere. The outbound agent is stated to operate across email and social channels, and nothing published states whether social messaging runs through that platform's sanctioned interfaces, through an automation layer, or by another route, nor whether any conformance position is held.

The grading convention treats undescribed automated activity against a professional network cautiously by default, and that is where this sits. The voice product adds a second platform dimension, since automated telephone origination depends on carrier and numbering arrangements that nothing published describes.

A third exposure follows from the subscription including a set number of contacts, which means the vendor supplies prospect data from a source it does not name, so a buyer inherits whatever collection basis that source operates under. Nothing suggests improper conduct; the point is that three distinct platform dependencies exist and none is described. Ask how social outreach is executed and under whose terms, what carrier arrangements underpin the voice product, and where the supplied contacts originate.

11x's June 2026 terms state that 11x "shall not use any Customer Data to train any artificial intelligence or machine learning models", and license customer data to 11x only to provide, maintain and improve the service. Customer data covers the contact lists and data sets a customer supplies as well as content generated in the service.

Performance data is treated separately: 11x may aggregate and analyze it to improve the service and use it in aggregated form, without identifying the customer, for its own marketing. No retention period is published; after termination each party returns or destroys the other's confidential information within seven days of a request, subject to backup and archival processes. No model provider is named, and no AI governance document or evaluation record is published for agents that write, send and speak in the customer's name.

The product is designed and marketed as a person, which makes this the most direct case of undisclosed machine authorship in this index. The agents carry human first names, are sold as workers a buyer hires rather than software they license, and are positioned explicitly against employing a human in the same role.

The outbound agent composes personalised email and social messages and handles replies, so a prospect can hold a multi turn exchange and reach a booked meeting without a person having participated. The voice agent conducts telephone conversations directly. Nothing published states whether recipients are told they are corresponding with or speaking to a system, whether disclosure can be enabled by the operator, or what either agent says if asked.

The naming convention is not incidental: presenting an automated system under a human name to a recipient who has no way to know otherwise is the specific practice this axis exists to record, and here it is the product's central design rather than a side effect. Two channels compound it, since a synthetic voice on a telephone call raises the question more sharply than email does. Ask whether the agents disclose that they are automated in email, social messages and on calls, and what each says when asked directly.

Little integration detail was reached on the routes taken this pass. Customer record integration is implied by the product's function, since an outbound agent booking meetings and tracking prospects must write somewhere, and independent analysis notes that the research layer depends on well defined target profiles and high quality customer record data to ground it, which indicates a real dependency on connected systems.

Beyond that inference nothing was established: no integration directory, connector list, developer documentation, interface reference or authentication model was located, and no marketplace or partner programme was found. This is a retrieval limit rather than a finding that integrations are absent, and a platform of this funding level almost certainly maintains connectors.

Independent analysis does add one relevant observation, that a competing research layer from a general purpose enrichment platform erodes this vendor's differentiation, which speaks to the ecosystem competitively rather than to its depth here. Ask for the integration list, the interface documentation, and which systems the agent writes to.

No deployment or residency information was reached on the routes taken this pass. No hosting provider or region is named, no European or United Kingdom residency election is described, no tenancy model is stated, and no recovery objective appears.

The gap carries weight in proportion to the corpus rather than the company size: the platform holds personal data on prospects across whatever territories a customer sells into, gathered and processed without those individuals' involvement, plus the correspondence and in the voice product the conversations that follow. A European prospect contacted by an agent has their details, the research conducted about them and their reply held somewhere the buyer cannot identify.

For a product sold on the premise of operating around the clock across every time zone, where the processing happens is a question the international positioning invites. Ask which regions host prospect data, research and correspondence, whether regional residency is available, and what the tenancy model is.

11x's security page states SOC 2 Type II, audited annually, with the detailed report available on request, and CASA Tier 3, covering identity and access management, data security, infrastructure, application security and incident management. Data sits on AWS with AES 256 encryption in RDS and TLS in transit, databases run in clustered configurations, and applications scale in containers. 11x states GDPR alignment with data processing agreements for EU customers, and CCPA compliance. No trust center, audit period, auditor, penetration test summary or subprocessor list is published.

11x publishes no pricing page, and its site routes every buyer to a live demo. The June 2026 terms describe how the service is sold without giving a price. Access is invoiced at the frequency set in the order form and includes a mutually agreed number of prepaid credits; credit purchases are non refundable, the service stops when the balance reaches zero after a low balance warning, and more credits are bought through a new order form. Invoices fall due within 30 days. No rate, credit price, plan or contract length appears on 11x's own pages, so a buyer cannot budget the purchase before the demo.

11x's June 2026 terms set the contract length in the order form and let either party terminate for a material breach left uncured for 30 days, or on insolvency. After termination, each party returns or destroys the other's confidential information within seven days of a request, subject to backup and archival processes, and the terms count customer data, including supplied contact lists and content generated in the service, as the customer's confidential information.

Credit purchases are non refundable. No export function, format or retrieval window is published for prospect research, sent messages, reply threads, call records or the exclusion lists a customer builds, and the public terms carry no renewal mechanics.

High volume autonomous sending with no published discipline, against a specific and widely reported quality complaint. Independent hands on testing recorded eight hundred and forty seven automated messages generated from two hundred leads over two weeks, which is sequence volume rather than spray, but nothing published describes the infrastructure behind it: whether messages leave from the customer's own connected mailboxes or vendor systems, who configures authentication records, whether warmup applies to a new sending identity, what bounce or complaint thresholds trigger intervention, or how one customer's sending is isolated from another's.

The reputational exposure is the finding rather than the volume. Competitive and user analysis converges on generic output as the consistent complaint, and generic output at scale from a domain a buyer owns is precisely how sender reputation degrades, which is the comparison one analysis draws directly against a human representative who would not burn the domain.

A buyer is therefore committing their own sending reputation to a system whose output quality they cannot evaluate before signing. Ask which infrastructure sends, whether warmup applies, what bounce thresholds stop the agent, and whether sending can be capped per day.

The fit statement that exists is written by third parties rather than the vendor, and it is narrower than the marketing. Independent analysis places the product with enterprise organisations that have budget to pilot, tolerance for reliability variance, a well defined target profile and high quality customer record data to ground the research layer, and that are willing to dedicate a revenue operations resource to configuring and monitoring agent behaviour.

It states equally plainly who should not buy, naming smaller companies requiring predictable guaranteed results. That last condition is the substantive one, because a product sold as replacing a hire that in practice requires an operations specialist to supervise is being bought for different economics than the pitch describes.

The vendor's own positioning has moved, with its blog acknowledging the debate between automated and human representatives and softening the earlier replacement framing. No industry pages, localisation or stated minimum deployment were located from the vendor. Ask what internal resource a deployment assumes, and what the smallest successful reference deployment looks like.