Agentforce Sales vs Evergrowth (2026)
The decision is which half of the motion you want the vendor to own, because these two split it in opposite directions. Agentforce Sales owns the send and not the data: its agent works the customer's own records grounded through the customer's own data platform, bundles no prospect database at all, and then researches, writes, sends and follows up inside the vendor's platform. Evergrowth owns the data and not the send: twelve specialist agents cascade through more than twenty third party data vendors for verified contact details, build the account plan and write the outreach, and the customer's existing engagement platform handles sequencing and delivery. So provenance is clean by construction at Agentforce and unstated at Evergrowth, while sending discipline belongs to somebody else entirely at Evergrowth and is an open question at Agentforce, where an agent sends at machine speed and nothing published describes warmup, volume governance or what happens when reputation degrades.
- Provenance has to be answerable in one sentence. No prospect database ships with the product. The agent works your own records grounded through your own data platform, so the origin of every contact is your own systems and the lawful basis question is one you already answered.
- You need the autonomy boundary written down rather than described. Admin defined engagement rules set when the agent may begin working a lead and how and when it may send, restricted lead suppression is a named control, a response violating a guardrail is withheld rather than shown, and an audit trail captures agent actions for governance review.
- Procurement will want documents before the first call. A public trust site carries compliance documentation, real time service status and a product level security, privacy and architecture document naming the agent products explicitly, all readable by an outsider without a commercial conversation.
- You need to name the model layer in a review. Evergrowth 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, and commits that there are no silent prompt or model swaps.
- The bill should not scale with headcount. There is no seat licence at all and 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, and the data waterfalls charged at a flat rate per verified result with failed lookups free.
- You want the exit defined before you sign. On cancellation the customer chooses whether data is returned or deleted, all personal data is permanently deleted within thirty calendar days where no request is made, and agent output synchronises continuously back into your own system of record.
Plain facts
| Agentforce Sales | Evergrowth | |
|---|---|---|
| Primary category | AI SDR & Outbound Agents | AI SDR & Outbound Agents |
| Founded | 1999 | 2014 |
| Headquarters | San Francisco, California, United States | New York, United States and Vilnius, Lithuania |
| Website | www.salesforce.com/agentforce/ | www.evergrowth.com |
Side by Side
| Axis | A Agentforce Sales |
E Evergrowth |
|---|---|---|
|
AI Capability
|
||
| AI Centrality | ||
| Autonomy and Oversight Model | ||
| AI Disclosure and Model Transparency | ||
| Operational and Outcome Evidence | ||
|
Compliance and Risk
|
||
| 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
|
||
| Ecosystem and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Security Certifications and Trust Center | ||
|
Commercial and Operational
|
||
| Commercial Transparency | ||
| Exit and Data Portability | ||
| Deliverability and Sending Discipline | ||
| Segment and Market Coverage | ||
The short version of each
Agentforce Sales
Agentforce Sales is Salesforce's sales product line, rebranded from Sales Cloud as the agentic layer became the headline, with a development agent that researches leads, drafts and sends outreach and books meetings, running on the underlying CRM and grounded in the customer's own records. The GTM Tech Index grades it A on autonomy and oversight, the most completely published autonomy boundary in the index, because admin defined engagement rules set when the agent may begin and how it may send, guardrail violations withhold the response rather than showing it, and an audit trail captures agent actions for governance review. The index grades it C on AI centrality, since the agent layer is separately licensed and metered but sits on a platform that works completely without it, and C on deliverability discipline, with no published account of warmup or volume governance under agent driven sending.
Source: GTM Tech Index, 2026
Evergrowth
Evergrowth is an agentic go to market workspace where a super agent called Eva runs twelve specialist agents that qualify accounts against a configured profile, research buying signals, verify employment, cascade through more than twenty data vendors for verified contact details 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. It also grades Evergrowth A on commercial transparency and A on exit and data portability.
Source: GTM Tech Index, 2026
Common questions
Is Agentforce Sales better than Evergrowth for AI sales development?
They divide the work differently, so the question is which half you want a vendor to own. Agentforce Sales owns the send and not the data: its agent works your own records, bundles no prospect database, and researches, writes, sends and follows up inside the Salesforce platform. Evergrowth owns the data and not the send: twelve specialist agents cascade through more than twenty third party data vendors, build the account plan and write the outreach, and your existing engagement platform sequences and delivers it. If you already run Salesforce and want fewer moving parts, the first. If you want new contacts and intend to keep sending where you send today, the second.
Where does the contact data come from in each product?
Agentforce answers it by construction and Evergrowth does not answer it at all. Agentforce bundles no prospect database; the agent works the customer's own records grounded through the customer's own data platform, so provenance traces to systems the buyer already owns. Evergrowth's waterfall cascades through more than twenty third party data vendors for verified email and phone and names none of them, with contact discovery reading the professional network, company websites and team pages and no source licence, lawful basis or collection method stated. The GTM Tech Index grades Agentforce B and Evergrowth C on that axis.
Do either say which AI models they use?
Evergrowth, by a distance, and it is the widest gap on this pair. It names five model providers outright, states each runs under contractual no training and no retention terms, rules out consumer endpoints and providers in non aligned jurisdictions by name, and publishes change control covering versioned system prompts and a commitment to no silent prompt or model swaps. Agentforce publishes a trust layer description and names third party model providers in its sub processor documentation, but does not enumerate which models sit behind particular agent actions, and its own privacy material notes that data masking, a headline trust layer control, is currently disabled for this product.
Which one protects my sending reputation?
Neither addresses it, for opposite reasons, and one of those reasons should worry a buyer more. Evergrowth does not send at all by design and states the boundary plainly, so sender reputation, authentication, pacing and complaint handling belong to the engagement platform downstream. Agentforce does send, at machine speed, and nothing published describes warmup, volume governance, rotation, spam rate monitoring or what happens when reputation degrades under agent driven volume. Implementation partner cost modelling notes a single sequence can run thirty five or more actions, which is a useful proxy for velocity and an unhelpful one for reputation.
How do Agentforce Sales and Evergrowth price?
Evergrowth publishes more completely and Agentforce publishes the smaller half of a bigger bill. Evergrowth carries the most complete commercial disclosure in the GTM Tech Index: no seat licence, unlimited users on every plan, a published credit cost for each of the twelve agents with 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. Agentforce publishes roughly 2 dollars per conversation, Flex Credits at 500 dollars per 100,000, and per user licensing from around 125 dollars a month, while the dependency that dominates the bill, the data platform the agents ground against, is not priced there and is independently reported as the largest and least predictable line.
How does the GTM Tech Index grade Agentforce Sales and Evergrowth?
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 Agentforce Sales A on autonomy and oversight, data privacy posture, AI safety and data stewardship, ecosystem depth, security certifications and segment coverage, and C on AI centrality because the agent layer sits on a platform that works completely without it. Evergrowth takes A on AI centrality, AI disclosure, safety and stewardship, commercial transparency and exit and data portability. Both hold C on recipient disclosure and authenticity and C on deliverability. 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 AI SDR & Outbound Agents page.
Neither vendor tells the person receiving the message that a machine wrote it, and the two arrive there from opposite ends. Evergrowth is the first vendor in this corpus to publish any position at all on the European artificial intelligence regulation, and the position is careful: the agents are stated not to make decisions in the high risk domains listed in Annex III, a human is stated to review any action affecting external parties, and outputs carry provenance and reasoning visible to the user.
Credit that before reading the qualification, because publishing a position and getting part of it wrong is a stronger place to stand than publishing nothing at all. Two things qualify it. The transparency described runs to the user rather than to the recipient, so nothing reaching the prospect discloses machine authorship.
And the article cited is Article 52, which is the numbering from the 2021 proposal rather than Article 50, the enacted provision in force since 2 August 2026, so the mapping appears to have been written against the draft and not revisited since.
Agentforce Sales publishes nothing on the point, which carries further here than it would for a smaller vendor: the European Commission's final Article 50 guidelines of 20 July 2026 place the marking obligation principally on the provider of the system rather than on the customer deploying it, and on this product the provider is Salesforce. Stated exposure under that regime reaches 15 million euro or 3 percent of worldwide turnover.
This index records what is published and asserts nothing about whether either company is compliant. Ask both what the recipient is told, and ask Evergrowth to confirm which article its mapping now tracks.