Evergrowth vs Regie.ai (2026)
The decision is what the system learns and from whom. Regie.ai's model learns one seller's voice from that seller's own sent mail, which is a genuine training disclosure telling the user precisely what personal data conditions the output, and it names nothing that generates it. Evergrowth runs the other way, naming five model providers outright, stating each operates under contractual no training and no retention terms, ruling out consumer endpoints and providers in non aligned jurisdictions, publishing versioned system prompts under change control and committing that there are no silent prompt or model swaps, while stating that customer records and agent activity never train any model including its own. So one vendor tells you what its model is fed and hides what it is, and the other tells you exactly what it is and commits that it is fed nothing of yours. The products divide the same way. Regie.ai runs one person's day and sends. Evergrowth writes the plays for a team and hands them to the sending platform you already run.
- No seat licence, and your team is going to grow. Every plan carries unlimited users with the price list denominated in credits per agent run, a published cost for each of the twelve specialist agents with low, medium and high effort tiers, three month rollover on monthly billing and a stated absence of overage penalties.
- You keep the sending platform you already run. Evergrowth writes the plays and your existing engagement platform sequences and delivers them, with bidirectional synchronisation into three named systems of record so agent output lands in your own records rather than only in the vendor's.
- Customer evidence should carry names and numbers. Six customers hold dedicated case study pages and five carry attributed quotes with name, title and employer, including one concrete figure: from eighty nine historic accounts the agents validated thirty seven as fitting the profile, and of two hundred and seventy eight contacts only four were still valid personas.
- The channel autonomy split has to be explicit rather than assumed. Regie.ai publishes it channel by channel: agents send the day's emails, calls land in the dialer for the human to place, and professional network touches arrive as tasks the seller sends personally rather than as automated messages.
- You want signals as well as a list. Account monitoring watches for job changes, funding rounds and leadership hires, and website visitor identification sits alongside cold outbound, inbound speed to lead and named account signals across six documented use case pages.
- Everything has to survive running out of credits. Regie.ai states the exhaustion behaviour plainly, that everything pauses and the prospects, drafts and settings stay exactly where they are, with self serve cancellation and its effective timing stated on the page.
Plain facts
| Evergrowth | Regie.ai | |
|---|---|---|
| Primary category | AI SDR & Outbound Agents | AI SDR & Outbound Agents |
| Founded | 2014 | 2020 |
| Headquarters | New York, United States and Vilnius, Lithuania | San Francisco, California, United States |
| Website | www.evergrowth.com | regie.ai |
Side by Side
| Axis | E Evergrowth |
R Regie.ai |
|---|---|---|
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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 | ||
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Integration and Deployment
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| Ecosystem and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Security Certifications and Trust Center | ||
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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
Evergrowth
Evergrowth is an agentic go to market workspace where a super agent runs twelve specialist agents that qualify accounts against a configured profile, research buying signals, find persona fit contacts, verify employment, build a communication style profile and write the outreach, while the customer's existing engagement platform does the sending. The GTM Tech Index grades it A on AI disclosure and model transparency, which nothing else in the index approaches: five model providers are named outright, each stated to run under contractual no training and no retention terms, with consumer endpoints and providers in non aligned jurisdictions ruled out by name and a published commitment to no silent prompt or model swaps. The index records one residual gap, that no accuracy or validation figure accompanies the account qualification score or the communication style profile.
Source: GTM Tech Index, 2026
Regie.ai
Regie.ai is a five year old venture backed vendor that has repositioned into an agentic workspace for individual sellers, where agents source prospects through a seven provider contact waterfall, monitor accounts for job changes and funding rounds, draft outreach trained on the seller's own sent mail, and dispatch from the seller's connected Gmail or Outlook rather than a vendor provisioned domain. The GTM Tech Index grades it C on AI disclosure and model transparency while crediting the one genuine training disclosure it makes: the drafting model learns the seller's voice from their own sent mail, which tells the user exactly what personal data conditions the output. Past that single sentence, no model provider, family or method is named anywhere, and no documentation describes how the waterfall ranks providers.
Source: GTM Tech Index, 2026
Common questions
Is Evergrowth better than Regie.ai for outbound?
They stop at different points in the day. Evergrowth writes the plays for a team, running twelve specialist agents that qualify accounts, research signals, verify employment and compose the outreach, and hands it to your existing engagement platform to sequence and deliver. Regie.ai runs one seller's whole day including the send, dispatching from their own connected mailbox with calls landing in a built in dialer. If you already have a sending platform you intend to keep, Evergrowth. If the seller has nothing and needs a queue tomorrow, Regie.ai.
Which one discloses what AI it runs on?
Evergrowth, by the widest margin in its sub lane. It names five model providers outright, states each operates under contractual no training and no retention terms, rules out consumer endpoints and providers in non aligned jurisdictions by name, publishes versioned system prompts under change control and commits that there are no silent prompt or model swaps. Regie.ai makes exactly one model disclosure, that the drafting model learns the seller's voice from their own sent mail, and names no provider, family or method anywhere.
Does my data train the models at either vendor?
Only Evergrowth answers it. It states that customer records, research outputs and agent activity are never used to train or fine tune any language model, that the sentence covers its own models as well as its providers', and that isolation is claimed separately for stored data and for vector retrieval so a query inside one customer environment cannot surface another's. Regie.ai holds the seller's prospect and conversation data in a built in system of record and reads their sent mail to train a personal writing model, and nothing published states whether that material trains anything shared or how tenants are isolated.
Where do Evergrowth and Regie.ai get contact data?
Both run a waterfall and neither names a supplier. Evergrowth cascades through more than twenty third party data vendors for verified email and phone, charged at a flat published rate per verified result with failed lookups free, and the customer needs no vendor subscriptions of their own. Regie.ai's waterfall is seven providers deep with mobile numbers, billed only when a lookup returns data, which admits plainly that the vendor resells third party data rather than claiming a proprietary database. Neither publishes a licence basis, collection method or refresh cadence for any of it.
How do Evergrowth and Regie.ai price?
Evergrowth publishes the more complete structure and Regie.ai the lower entry point. Evergrowth has no seat licence at all and unlimited users on every plan, with a published credit cost per agent, effort tiers, waterfall lookups at a flat rate per verified result with failures free, four tiers in three currencies, and both a credit simulator and a return calculator, which the GTM Tech Index grades A. Regie.ai publishes a free tier with two hundred and fifty credits and a professional tier at forty nine dollars monthly with five thousand credits, and no credit schedule, so what a lookup or a drafted message costs cannot be established.
How does the GTM Tech Index grade Evergrowth and Regie.ai?
Both are graded on the same seventeen capability and compliance axes from public sources, and both sit at full documented depth with every axis graded above the floor. The GTM Tech Index grades Evergrowth A on AI centrality, AI disclosure and model transparency, AI safety and data stewardship, commercial transparency and exit and data portability. Regie.ai takes A on AI centrality and B on autonomy and oversight, platform terms exposure, ecosystem depth, security certifications, commercial transparency, deliverability discipline and segment coverage. 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 Data & Enrichment page.
Both products build a profile of a named individual from that person's own writing, and the individuals are different, which is worth separating carefully. Evergrowth's agents read a prospect's professional network posts, shares and engagement and derive a communication style profile used to calibrate the message sent to them. That person never contracted with anyone.
The vendor's own data minimisation list enumerates full name, job title, email, phone and professional profile without mentioning the derived profile, and no notice route or removal path is published for the individual. Credit the minimisation discipline, which ships as a constraint rather than being stated as a principle, and note that the derived layer sits outside it. Regie.ai's subject is the customer's own employee.
Its drafting model reads the seller's sent mail to learn their voice so the output reads as though they wrote it, which is a genuine training disclosure telling the user exactly what personal data conditions the output, and nothing published states retention or processing terms for that corpus, what happens to the voice model when the seller leaves the company, or whether it transfers with the seat.
Ask Evergrowth what a prospect can do to be removed, and ask Regie.ai what becomes of a departing employee's voice model. The shared silence sits underneath both: neither vendor publishes an accuracy figure, a validation method or any confidence treatment for the inferences its system draws about a person, and at both companies those inferences are handed to a seller or written into a message as though settled.