Sailes vs Selix AI (2026)
The decision is whether the agent asks. Selix AI works out of a team messaging channel, posting what it is researching and what it plans next, asking when it reaches a decision that benefits from human judgement, and surfacing proposed actions for review before anything executes. Sailes runs the opposite design and states it without hedging: hands free, end to end, no human in the loop, with the representative entering only when a qualified lead is delivered. Each Sailes agent is built to mirror one named person's communication style, sends under that person's identity, and reads and answers replies and objections in their name without their involvement in the exchange. Both vendors state that their agents improve over time, and neither publishes whether that learning stays inside the tenant it came from, which is the question an enterprise buyer asks first and the one neither answers.
- You are replacing a function rather than adding a tool. Sailes names enterprise customers across consumer products manufacturing, energy, waste management, industrial automation, pharmaceuticals and academic publishing, and describes a specific deployment pattern, one agent paired to one account executive as an alternative to the development representative model.
- You need a leader's view across a fleet rather than one operator's console. A command centre separates leader and user roles, onboards representatives, deploys and trains agents, filters campaigns between active and finished, and reports individual agent performance and labour savings to leadership.
- You want the boundaries of an autonomous system to be settings you control. Targeting is bounded by customer defined keywords, job titles, industries and geography, with campaign level pre approval of target companies, which are real constraints expressed as product surfaces rather than as assurances in marketing copy.
- The agent should ask rather than assume. Selix posts its reasoning into a team messaging channel as it works and stops for human judgement when it reaches missing information, so oversight is ambient and visible to the whole team rather than sitting in one person's approval queue.
- Sending identity matters to your risk case. Selix sends through infrastructure the customer controls under their own sending identity with warming applied to their own mailboxes, and publishes no rented accounts, persona or synthetic sender, where its counterpart does not state whose domain carries the volume at all.
- You want a privacy document that reaches the product. Selix's statement enumerates lawful bases against each processing purpose, names standard contractual clauses, operates a data subject rights portal, and discloses a sale of identifiers and inferences under the Californian definition, which is adverse and published rather than concealed.
Plain facts
| Sailes | Selix AI | |
|---|---|---|
| Primary category | AI SDR & Outbound Agents | AI SDR & Outbound Agents |
| Founded | Not published | 2022 |
| Headquarters | Kansas City, Missouri, United States | San Jose, California, United States |
| Website | sailes.com | selix.ai |
Side by Side
| Axis | S Sailes |
S Selix AI |
|---|---|---|
|
AI Capability
|
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| AI Centrality | ||
| Autonomy and Oversight Model | ||
| AI Disclosure and Model Transparency | ||
| Operational and Outcome Evidence | ||
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Compliance and Risk
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| Outreach Compliance Posture | ||
| Data Privacy Posture | ||
| Data Licensing and Provenance | ||
| Platform Terms Exposure | ||
| AI Safety and Data Stewardship | ||
| Recipient Disclosure and Authenticity | ||
|
Integration and Deployment
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| Ecosystem and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Security Certifications and Trust Center | ||
|
Commercial and Operational
|
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| Commercial Transparency | ||
| Exit and Data Portability | ||
| Deliverability and Sending Discipline | ||
| Segment and Market Coverage | ||
The short version of each
Sailes
Sailes builds autonomous prospecting agents paired one to one with individual sales representatives, each configured against targeting parameters its representative sets and built to mirror that person's communication style, running research, contact sourcing, message generation, sending, reply handling and meeting scheduling without a human in the loop. The GTM Tech Index grades it A on AI centrality, noting that the company was building this before the category existed and that production history under enterprise load is a stronger signal than a recent launch, and B on autonomy and oversight for a command centre with a leader and user role split and campaign level pre approval of target companies. The index grades it D on data privacy posture because the published policy declares that the product sits outside its own scope and points to separate terms that are not published anywhere.
Source: GTM Tech Index, 2026
Selix AI
Selix AI is an outbound agent from SellScale, Inc. that runs out of a team messaging channel rather than a console, posting what it is researching and what it plans to do next, asking when it reaches missing information or a decision that benefits from human judgement, and surfacing proposed actions for review before anything executes. The GTM Tech Index grades it A on AI centrality and B on autonomy and oversight, recording the narration design as better than a conventional approval gate because the operator sees intermediate steps rather than only the finished artefact and the exchange sits where the team can see it. It also grades Selix C on data privacy posture, crediting a rights apparatus that enumerates lawful bases per purpose and operates a request portal, alongside a disclosed sale of identifiers and inferences under the Californian definition.
Source: GTM Tech Index, 2026
Common questions
Is Sailes better than Selix AI for autonomous prospecting?
They are opposite designs and the vendors say so plainly, which makes this unusually easy to decide. Sailes runs hands free end to end with no human in the loop, and the representative enters only when a qualified lead is delivered. Selix works out of a team messaging channel, narrating what it is researching, asking when it reaches a decision that benefits from human judgement, and surfacing proposed actions for review before anything executes. If you want a function replaced, Sailes is built for that and names enterprise customers who bought it that way. If you want a machine that stops and asks, Sailes does not do that and does not claim to.
Does Sailes send emails in my name without me seeing them?
Sailes does, and it is the product's central claim. Each agent is built to mirror the personality, communication style and selling approach of one named person, the vendor illustrating that an assertive salesperson can develop an equally assertive agent, and emails send in that person's identity while the agent reads replies and handles objections without their involvement in the exchange. No disclosure statement, automation notice or position on identifying the sender as an agent appears anywhere. Selix also sends under the customer's own identity and likewise publishes no disclosure, though it makes no claim to mirror a specific individual.
How much productivity does Sailes actually deliver?
The published figures do not reconcile with one another, and the GTM Tech Index records that as the finding. Four different magnitudes appear across the vendor's own materials for the same product: a second generation launch described as a 130 percent efficiency improvement, an annual study headlined as a ninefold productivity gain whose own address line claims 3,000 percent, and a home page claiming sixteen times the output of a human representative. That spans roughly 1.3 times to 30 times. A separate claim of 1,920 hours saved per month per agent exceeds the total hours in a month by more than double. No methodology, measurement period or sample supports any of them.
How much do Sailes and Selix AI cost?
Neither publishes a price. Sailes routes every commercial path to a custom demo request, with a third party directory reporting pricing determined by the number of agents and no free trial, and the vendor's own site is titled around guaranteed return on investment and publishes a return calculator while withholding the one input the model needs. Selix's terms of service state that fees are set out in an order or will otherwise be communicated to the customer. The GTM Tech Index grades both D on commercial transparency.
Do Sailes or Selix AI say what AI they are built on?
Neither names a provider, and both describe an architecture instead. Sailes describes an ensemble combining natural language comprehension, neural networks and multiple transformer models with an aggregation layer and a named cognition component, which is more than most of this category attempts, but no provider, version identifier, evaluation or accuracy measure appears. Selix markets the product as a superintelligence while its lengthy privacy statement contains no section on model use at all. The unanswered question at both is whether one customer's replies and outcomes improve a model that also serves another.
How does the GTM Tech Index grade Sailes and Selix AI?
Both are graded on the same seventeen capability and compliance axes from public sources. Both take A on AI centrality and B on autonomy and oversight, and both take B on segment and market coverage. The GTM Tech Index separates them on documentation depth: Selix holds C on data privacy posture, recipient disclosure and authenticity, and ecosystem and integration depth, where Sailes holds D on the first two and C on the third, and Selix holds B on deliverability discipline where Sailes holds D. Sailes holds C on AI disclosure and model transparency against D for Selix. The index publishes no composite score and declares no winner.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Sales Engagement & Outreach page.
Sailes's privacy policy excludes the product from its own scope, and that is the most consequential line on either record. The document declares in its opening section that it applies to information collected on the website and in messages between the reader and the vendor, then states that specific product offerings, naming the command centre platform, involve third party personal information provided by users and are covered by separate terms and conditions.
No such separate document is published anywhere. Every substantive protection in the policy, the state rights sections, the deletion route, the sale opt out and the response timings, attaches to website visitors rather than to the prospects the product sources, enriches, profiles and emails. Ask for the product terms in writing before any evaluation begins.
Two internal contradictions sit alongside it: the consumer categories table records that no network activity is collected while the section immediately preceding it describes collecting browsing actions, resources accessed and address information, and the same table records that no inferences are drawn about individuals while inferring fit and intent about individuals is the product's core function.
Selix discloses more and is credited for it, including a sale of identifiers, network activity and inferences to advertising networks and analytics providers under the Californian definition, which is adverse and stated rather than concealed. The shared silence is what the learning touches.
Both vendors state that their agents improve over time, Sailes through personalisation trained to mirror an individual representative's writing and Selix through accumulated targeting, and neither publishes a tenant isolation commitment, a training corpus, or what becomes of a trained agent when the person it mirrors leaves the company.