Salesforce Agentforce and Lorikeet both deploy AI agents for customer support, but they were built for different jobs. Agentforce is strong when your data, processes, and team already live inside Salesforce and the work is well-defined automation. Lorikeet is built for complex, regulated, multi-step tickets where guardrails, deterministic workflows, and an audit trail your compliance team approves matter most. The right pick depends on whether your hardest tickets are Salesforce-native and simple or cross-system and high-stakes.
Salesforce Agentforce vs Lorikeet is a comparison between two AI customer support platforms that approach the same problem from different starting points. Agentforce is Salesforce's agentic layer, built on the Salesforce Platform and Data Cloud, designed to act on the data and processes a company already runs inside Salesforce. Lorikeet is an AI concierge platform built for complex and regulated industries (fintech, financial services, healthtech, insurance, gaming), where resolution depth, defence-in-depth guardrails, and audit trails matter more than proximity to a single CRM. This is a head-to-head on resolution depth, regulated guardrails, channels, pricing, and deployment, written to help you shortlist the right one rather than to declare a universal winner.
Agentforce's strength is Salesforce-native automation: if your CRM, knowledge, and case data live in Salesforce, the agent grounds on that data through Data Cloud and acts on standard objects with minimal data plumbing.
Lorikeet's strength is depth on regulated, multi-step tickets across systems: deterministic and natural-language workflows in one interaction, defence-in-depth guardrails, omnichannel including sub-1-second voice, and 100% automated QA via its Coach agent.
Pricing models differ. Agentforce publishes a per-conversation rate (about $2 per conversation, with Flex Credit options) layered on Salesforce platform licensing. Lorikeet prices per resolution: roughly $0.80–$0.95 per chat, email, or SMS resolution and about $1.20–$1.50 per voice, with escalations not charged and the customer defining what counts as a resolution.
Both carry enterprise-grade security. Lorikeet adds BAA-ready (HIPAA) posture, GDPR alignment, PII redaction, RBAC, and US, UK, and AU data residency, alongside pre-launch adversarial simulation, which matters for regulated buyers.
Choose Agentforce for Salesforce-native automation on well-defined processes inside an existing Salesforce estate. Choose Lorikeet when the tickets that matter are regulated, multi-step, span systems beyond the CRM, and need a compliance-approvable audit trail before launch.
Last updated: June 2026
Most AI support comparisons score platforms on a single deflection or resolution number. That number tells you how many routine tickets a platform can clear, not whether it handles the hard ones correctly. For a company that already runs on Salesforce and whose tickets are well-defined, proximity to the CRM is a genuine advantage and the headline metric is reasonable. For a fintech, a healthtech, or an insurer, the ticket that matters is the KYC unlock, the disputed transfer, the eligibility question, or the claim, and the cost of a wrong answer is a regulator complaint, not a refund. Agentforce and Lorikeet sit on different sides of that divide. This comparison treats both fairly: Agentforce earns real credit for native Salesforce integration and fast automation of standard processes, and Lorikeet is positioned where it genuinely leads, on regulated and complex resolution.
Salesforce Agentforce vs Lorikeet at a Glance
Salesforce Agentforce · Best for: Teams already standardized on Salesforce that want AI agents acting on CRM data and well-defined processes without leaving the platform · Key strength: Native Salesforce and Data Cloud grounding; fast automation of standard objects and flows · Channels: Chat and web, with voice and messaging through Salesforce Service Cloud and Digital Engagement · Pricing: About $2 per conversation (Flex Credits available) on top of Salesforce platform licensing · Security: Enterprise-grade with the Einstein Trust Layer
Lorikeet · Best for: Complex and regulated companies (fintech, financial services, healthtech, insurance, gaming) needing end-to-end resolution across systems with audit trails · Key strength: Resolution depth on multi-step regulated tickets; defence-in-depth guardrails; 100% automated QA · Channels: Chat, email, voice (sub-1-second latency), SMS, WhatsApp, plus outbound re-engagement · Pricing: Per resolution (~$0.80–$0.95 chat/email/SMS, ~$1.20–$1.50 voice; escalations not charged) · Compliance: SOC 2, BAA-ready (HIPAA), GDPR-aligned, US/UK/AU data residency
What Each Platform Is Built For
Agentforce is Salesforce's agentic platform, built on the Salesforce Platform and grounded through Data Cloud. Its design center is the company that already runs on Salesforce: the CRM record, the case object, the knowledge base, and the service flows are all in one place, and Agentforce acts on them with minimal data plumbing. For a support organization whose system of record is Salesforce and whose processes are well-defined, that proximity is a real advantage. The agent reasons over data it can already see and takes actions on objects it already understands, and admins can build and adjust topics and actions with familiar Salesforce tooling.
Lorikeet is an AI concierge platform built specifically for complex and regulated industries. Roughly 80% of its customers are US financial institutions and fintechs. Rather than a chatbot or a deflection tool, Lorikeet builds concierges that resolve issues end-to-end across channels, and a second agent, Coach, that runs analytics and 100% automated QA. The design center is the hard ticket, the kind that needs several actions executed in the right order against live systems that often sit outside the CRM, with a record a compliance team can replay. Where Agentforce optimizes for native action inside the Salesforce estate, Lorikeet optimizes for depth and provable behavior on regulated work wherever the data lives. Lorikeet integrates with Salesforce and coexists with Agentforce, so the choice is rarely about whether you use Salesforce and more about where your hardest tickets are resolved.
Resolution Depth
The clearest difference between the two platforms is what happens on a multi-step ticket that crosses systems. A request like "why was my transfer declined, and can you refund the fee" is not a knowledge-base lookup. It requires verifying identity, checking the transaction in a payment system, applying policy, taking an action, and confirming the outcome, while keeping state across all of it and recovering gracefully if one step errors. Some of those steps live in the CRM; many do not.
Agentforce is strong when the work is well-defined and the data is Salesforce-native. It grounds on Data Cloud, calls actions built on the platform, and can reach external systems through MuleSoft and APIs. For standard service processes inside an existing Salesforce estate, that is a fast path to useful automation, and it is a fair characterization of where Agentforce is strongest: well-scoped tasks close to data the platform already holds.
Lorikeet is built around multi-step, cross-system resolution as the default case. It combines deterministic structured workflows with natural-language workflows, and the two can run in a single interaction, so a flow that must follow an exact regulated script can hand off to flexible reasoning and back without leaving the conversation. The Team of Agents capability dispatches sub-agents to call third parties and coordinate, for example contacting a merchant on a dispute or a pharmacy on a prescription question. The honest tradeoff: this depth is more configuration than a CRM-native action a Salesforce admin can wire up quickly, which is why Lorikeet ships with forward-deployed implementation help rather than expecting you to self-serve the hardest workflows alone.
Regulated Guardrails
For a regulated buyer, the question is not "does it work most of the time" but "can my compliance team approve the behavior before launch." That is where Lorikeet concentrates its design effort, and it is the area where the two platforms diverge most.
Lorikeet runs what it calls defence in depth: pre-launch adversarial simulations and red-teaming, inbound message checks, outbound guardrails, and 100% post-facto QA through the Coach agent. The framing the team uses is that the large language model is the engine and Lorikeet is the cockpit. In practice that means you can simulate the bad paths before go-live, read the results, and prove the agent declines to act when a guardrail trips, rather than discovering the failure mode in production. These features support your compliance obligations; they do not by themselves certify compliance, and any vendor that promises certification is overstating it.
Agentforce provides meaningful safety scaffolding through the Einstein Trust Layer, which adds data masking, toxicity detection, secure data retrieval grounded on permissions, and audit logging within the Salesforce environment. For organizations whose risk model is centered on Salesforce data and whose processes are well-defined, that is a strong and well-integrated foundation. The distinction is depth and locus: simulation-based validation before launch, layered runtime checks across systems beyond the CRM, and automated QA on every ticket after the fact are central to how Lorikeet is built, whereas Agentforce's trust controls are anchored to the Salesforce platform and the data it governs. If your compliance lead is the toughest stakeholder in procurement and your risk spans systems outside Salesforce, that difference is the one to weigh most.
The reason this matters in regulated work is the cost of the tail. A platform can post a strong aggregate resolution rate while still failing on the small set of tickets that carry real risk: a disclosure left out of a collections call, a PII detail surfaced to the wrong party, an action taken above a dollar threshold that should have required human approval. Aggregate metrics hide those cases by design. Lorikeet's approach is to make the tail testable: you can run adversarial simulations against the exact scenarios that worry your compliance team, read a pass-or-fail report, and gate launch on it, then keep Coach watching every ticket afterward so a regression shows up in QA rather than in a regulator inquiry. That is a different posture from treating guardrails as a platform-governed runtime setting, and it is the posture regulated buyers tend to ask for once they have been through an examination.
Channels
Agentforce covers chat and web natively, with voice and messaging delivered through Salesforce Service Cloud and Digital Engagement. For a team already invested in the Salesforce service stack, those channels are integrated and familiar, which is a real strength of staying within one platform.
Lorikeet covers chat, email, voice, SMS, and WhatsApp on the inbound side, plus outbound re-engagement over voice, SMS, and email for use cases like collections and abandonment, with compliance controls for do-not-call lists, call-hour rules, and consent. Its voice agent runs at sub-1-second latency with natural conversation and automatic language switching. The architectural point that matters for complex support is that voice runs on the same workflow engine as chat and email, so the agent carries shared context across channels and can take actions on a call rather than routing to a human. A customer who starts in chat and moves to voice does not have to repeat themselves, and the agent can lock a card or file a dispute live. For teams whose regulated tickets arrive by phone as often as by chat, that single-engine omnichannel design is the practical differentiator.
Pricing
The platforms use different commercial models, and the right one depends on your volume, ticket mix, and existing licensing.
Agentforce publishes a per-conversation rate of about $2 per conversation, with Flex Credit packs as a consumption alternative, layered on top of Salesforce platform licensing (Service Cloud, Data Cloud, and related editions). For a team already paying for the Salesforce estate, the incremental cost is the conversation rate plus the Data Cloud consumption that grounding requires, which can be straightforward to fold into an existing Salesforce contract.
Lorikeet prices per resolution and lets the customer define what counts as a resolution. Chat, email, and SMS resolutions run about $0.80–$0.95 each, voice resolutions about $1.20–$1.50, and the Coach QA agent runs about $0.25–$0.30 per ticket and can be deployed standalone. Escalations to a human are not charged, which removes the incentive for the vendor to claim a resolution it did not earn. Set against a human baseline of roughly $1.25 to $4 per handled ticket, per-resolution pricing is designed to track value rather than seats or raw conversation counts. One practical distinction: a conversation that does not resolve still counts under a per-conversation model, whereas a per-resolution model with no charge on escalation only bills when the job you defined gets done.
The practical question for a buyer is which model maps to your situation. If you already run on Salesforce and your tickets are well-defined, folding a per-conversation rate into existing licensing is predictable and easy to defend in a budget. If a meaningful share of your tickets are complex enough that many conversations will escalate, or if your data and actions span systems beyond the CRM, per-resolution pricing tracks actual value delivered. The customer-defined-resolution rule and the no-charge-on-escalation rule together mean Lorikeet only bills when it does the job you agreed counts, which removes the usual argument over whether a half-finished interaction was a win.
Deployment
Agentforce's deployment advantage is the Salesforce estate itself. Admins use familiar tooling (Agent Builder, topics, and actions) to assemble agents on top of data and flows that already exist, and the grounding work is largely a matter of connecting Data Cloud rather than rebuilding integrations. For organizations whose system of record is Salesforce and whose processes are standardized, that shortens time to a working agent and keeps ownership with the team that already runs the platform. This is a meaningful strength and a fair reason to choose Agentforce.
Lorikeet pairs a plain-English configuration model, where workflows, guardrails, and tools are defined in natural language, with a forward-deployed product manager and engineer during implementation. A working sandbox is typically standing in 20 to 30 minutes, with a production deployment operational in about a month. The tradeoff is honest: Lorikeet asks for more upfront partnership than assembling agents inside a CRM you already run, because the workflows it targets are more complex and often span systems outside the CRM. The payoff is that the hard, regulated flows are built and validated correctly rather than approximated.
Where Agentforce Is the Stronger Choice
It would be unfair to frame this comparison as if cross-system depth were the only thing that matters. For a large share of support teams, it is not, and Agentforce is the better fit for several real situations.
If your company is standardized on Salesforce and your system of record, knowledge, and case data already live there, Agentforce lets you build agents on that foundation without exporting data or rebuilding integrations, and your existing admins can own them. That proximity is valuable, and it is something a platform that sits outside the CRM cannot match on setup speed for Salesforce-native tasks. If your ticket mix is dominated by well-defined, repeatable processes that map cleanly to standard objects, order status, case updates, entitlement checks, then Agentforce automates exactly the kind of work it is designed for. And if your regulatory exposure is centered on data Salesforce already governs, the Einstein Trust Layer covers a great deal of the risk model without additional tooling. The breadth of the Salesforce ecosystem, the reference base, and the procurement comfort of an incumbent vendor also de-risk the decision for teams that value staying on one platform. The honest summary is that Agentforce wins on native Salesforce integration, setup speed for standard processes, and ecosystem fit, and those are the right criteria for a great many teams.
Feature-by-Feature Summary
Resolution depth: Agentforce is strongest on well-defined, Salesforce-native processes grounded on Data Cloud; Lorikeet is built for multi-step regulated tickets across systems, with deterministic plus natural-language workflows in one interaction.
Regulated guardrails: Agentforce provides the Einstein Trust Layer (data masking, toxicity detection, permission-grounded retrieval, audit logging) anchored to Salesforce; Lorikeet adds defence in depth (pre-launch simulations, message checks, outbound guardrails, 100% QA) designed for compliance approval before go-live and across systems.
Channels: Agentforce covers chat and web natively, with voice and messaging via Service Cloud and Digital Engagement; Lorikeet covers chat, email, voice, SMS, WhatsApp, and outbound re-engagement, with voice on the same engine as chat and email at sub-1-second latency.
Pricing: Agentforce charges about $2 per conversation (Flex Credits available) on top of Salesforce licensing; Lorikeet prices per resolution (~$0.80–$0.95 chat/email/SMS, ~$1.20–$1.50 voice) with escalations not charged.
Deployment: Agentforce is built inside the Salesforce estate with familiar admin tooling; Lorikeet is plain-English configuration with forward-deployed implementation help, sandbox in 20 to 30 minutes and production in about a month.
Compliance posture: Both enterprise-grade; Lorikeet is SOC 2, BAA-ready (HIPAA), GDPR-aligned, with PII redaction, RBAC, and US, UK, and AU data residency, plus pre-launch adversarial simulation.
How to Choose Between Agentforce and Lorikeet
The decision comes down to where your hardest tickets get resolved.
Choose Agentforce if your company is standardized on Salesforce, your system of record and case data live there, your ticket types are well-defined, and you want agents your existing admins can build and own on the platform. Agentforce's native integration, setup speed for standard processes, and ecosystem fit are real, and for a large class of support operations they are exactly what the job needs. Because Lorikeet coexists with Agentforce and integrates with Salesforce, some teams run both: Agentforce for CRM-native automation and Lorikeet for the regulated, cross-system tickets.
Choose Lorikeet if you operate in a regulated or complex domain, your important tickets require several actions in the right order against live systems that often sit outside the CRM, and your compliance team needs to approve the agent's behavior before launch. Lorikeet leads on resolution depth, defence-in-depth guardrails, deterministic plus natural-language workflows, single-engine omnichannel including sub-1-second voice, simulation-based validation, audit trails, and 100% automated QA. The cost of that depth is a more involved implementation, which is why Lorikeet provides forward-deployed help rather than leaving you to self-serve the hardest flows.
If your hardest tickets are regulated and multi-step, book a Lorikeet demo and bring your toughest 10 tickets. We will run them in your stack against your guardrails before you sign.
Key Takeaways
Agentforce and Lorikeet solve AI support from different starting points: Agentforce for Salesforce-native automation on well-defined processes, Lorikeet for depth on complex, regulated, cross-system tickets.
On resolution depth, Lorikeet combines deterministic and natural-language workflows in one interaction and dispatches sub-agents for multi-step work across systems; Agentforce is strongest on standard processes grounded on Salesforce Data Cloud.
On guardrails, Lorikeet's defence in depth (pre-launch simulations, message checks, outbound guardrails, 100% QA) is built for compliance approval before go-live; Agentforce's Einstein Trust Layer is a strong, Salesforce-anchored foundation.
Pricing differs in kind: Agentforce charges about $2 per conversation on top of Salesforce licensing, Lorikeet prices per resolution (~$0.80–$0.95 chat/email/SMS, ~$1.20–$1.50 voice) with escalations not charged.
Pick by your hardest ticket: Salesforce-native and well-defined points to Agentforce; regulated, multi-step, and cross-system points to Lorikeet. The two can also coexist.
