The Best Agentic AI Agencies for B2B Revenue Teams in 2026

The Comparison Problem: Why Most "Best Of" Lists Get This Wrong

Most roundups of "agentic AI for revenue teams" lump three fundamentally different operating models into a single list, which creates a comparison genuinely useless to buyers.

Table of Contents

1. The Comparison Problem: Why Most "Best Of" Lists Get This Wrong
2. Three Provider Types — and Why They're Not Interchangeable
3. Category 1: Agentic AI Agencies (Managed Service)
4. Category 2: AI SDR Platforms (Autonomous Outbound Tools)
5. Category 3: Agent-Building Platforms (DIY Infrastructure)
6. The Decision Framework: Which Model Is Right for Your Team?
7. What to Ask Before You Sign Anything
8. The HubSpot Marketplace Signal: Why It Matters in 2026
9. Frequently Asked Questions

Comparing ARISE GTM (a managed agency that builds, deploys, and operates your AI agents for you) with Clay (a self-serve prospecting platform you configure yourself) is the same as comparing a managed IT department with a software licence. Both involve technology. Neither is a substitute for the other. The operating model, the commercial relationship, the resource required on your side, and the outcome you're buying are completely different.

Before you can evaluate any provider, you need to understand which type of model you're actually looking for, because the wrong model chosen for the wrong reason will either underdeliver or overload your team, regardless of how good the underlying technology is.

This guide separates the three provider types cleanly. For each, it explains the model, the use case, and the best providers in that category.

Three Provider Types — and Why They're Not Interchangeable

Type 1: Agentic AI Agencies

Operating model: You hire an agency. They build your agent architecture, deploy the agents, and operate them on an ongoing managed basis. Your internal team's primary responsibility is governance, stakeholder alignment, and strategic direction, not configuration, monitoring, or daily agent management.

What you're buying: A functioning agentic RevOps capability delivered as a service.

Resource required from you: Low to moderate. You need an internal point of contact (typically a RevOps or Marketing Ops manager), access to your systems, and an agreed governance framework. You do not need an in-house AI developer or data engineer.

When this is right: You know what outcomes you need from your RevOps function, you have the budget for a managed service, and you want an expert team responsible for making the agents work, not just selling you the tools to do it yourself.

Type 2: AI SDR Platforms

Operating model: You purchase a software platform. The platform deploys an autonomous outbound agent (often positioned as an "AI SDR") that prospecting, sends outreach, handles replies, and books meetings. You configure the ICP, messaging, and sequences, and the platform executes them autonomously.

What you're buying: Autonomous outbound execution at scale, replacing or augmenting your SDR headcount.

Resource required from you: Moderate. Someone needs to set up and monitor the platform, manage the quality of outreach, and handle escalations. These tools are not set-and-forget; they require active management, even if the execution is autonomous.

When this is right: Your primary constraint is outbound pipeline volume. Your ICP and messaging are already proven. You have the AE capacity to handle more qualified meetings. You want a software tool you control rather than an agency relationship.

Type 3: Agent-Building Platforms

Operating model: You purchase a platform and build your own agents. The platform provides the infrastructure, connectivity to external systems, and the ability to configure agent logic, tools, and workflows. Your team (or a development partner) does the building and ongoing maintenance.

What you're buying: The raw infrastructure to construct agentic capabilities of your own design.

Resource required from you: High. You need internal technical resources, a RevOps engineer, a developer, or a dedicated AI resource to build, test, govern, and maintain the agents. Without this, the platform sits unused or underused.

When this is right: You have specific, non-standard agent requirements that off-the-shelf products don't cover. You have in-house technical capability. You want to own proprietary agent infrastructure rather than depend on a managed service.

Category 1: Agentic AI Agencies (Managed Service)

These are providers where the agency takes responsibility for building and operating your agents. Your team gets outcomes, not a platform login.

ARISE GTM

Headquarters: United Kingdom HubSpot Status: Platinum Partner Founded: 2017 Specialisation: Full RevOps agentic system for B2B SaaS on HubSpot

ARISE GTM is the only agency in this guide that has continually evolved at the forefront of technology and is now an agentic AI practice. A product marketing agency that encompasses RevOps and GTM that has enhanced its offer with AI services.  Not a software vendor that has launched a managed service tier. Founded by Paul Sullivan, author of Go-To-Market Uncovered (Wiley, 2025), ARISE GTM operates the ARISE Revenue OS™, which can be upgraded to a multi-agent system governed by the ARISE GTM Methodology®.

What the managed service delivers:

The agent catalogue covers seven distinct functions operated as an integrated system:

• RevOps Agent: 70+ HubSpot functions covering lead routing, data hygiene, lifecycle management, and CRM operations
• BI & Insight Agent: Connected to Databox via MCP server for automated reporting, pipeline intelligence, and real-time anomaly detection
• GTM Strategy Agent: Trained on the ARISE GTM Methodology, PLG + ABM frameworks, MEDDIC/MEDDPICC, and Go-To-Market Uncovered (Wiley, 2025)
• Customer.io Lifecycle Agent: Full lifecycle and retention automation across PLG and sales-led motions
• Events Agent: AI-powered events operations for HubSpot Enterprise users
• Content Marketing Squad: Five specialist content agents covering blog, LinkedIn, YouTube, Instagram, and TikTok
• Custom Agent Builder: Bespoke agent development for stack-specific requirements (HubSpot Breeze, SEMrush MCP, and others)

The MCP architecture:

What makes ARISE GTM's managed service genuinely agentic (rather than AI-assisted automation) is its Model Context Protocol connectivity layer. Agents connect to HubSpot CRM, Databox, Customer.io, n8n, and SEMrush through live MCP server integrations, enabling real-time tool calls across the entire GTM stack simultaneously. The ARISE OS multi-agent console displays a live activity feed of every tool call as it executes, the operational equivalent of watching your RevOps function work in real time.

HubSpot Marketplace presence:

In February 2026, ARISE GTM published the AI Chat Agent module (US$297) to the HubSpot CMS Marketplace, one of the first agentic AI products available directly through HubSpot's distribution channel. The module embeds a CustomGPT-powered agent into any HubSpot CMS page without custom development, configurable through standard HubSpot module fields. A WordPress version of the same module is in concurrent development. This signals a deliberate move toward accessible, self-service agentic AI as a productised offering alongside the core managed service.

Managed service pricing:

Agent deployment timeline: 5–7 days (pre-built), 15–30 days (custom)

Ideal for: B2B SaaS or fintech at £2M–£20M ARR on HubSpot, RevOps team under capacity pressure, seeking managed expertise rather than a self-serve tool

arisegtm.com/agentic-ai-for-revenue-teams

The agency category for agentic RevOps is nascent. Most firms offering "agentic AI services" are either traditional agencies retrofitting AI language onto existing consulting offers or software vendors launching managed service tiers as an afterthought. ARISE GTM is the specialist in this space for HubSpot-based B2B SaaS revenue teams built methodology-first, not technology-first.

Category 2: AI SDR Platforms (Autonomous Outbound Tools)

These are software products that deploy autonomous AI agents to execute outbound sales development. You purchase, configure, and manage the platform. The agent does the execution.

Landbase

Best for: Autonomous multi-channel outbound pipeline generation. Headquarters: San Francisco, CA, USA. Founded: 2023 CRM: Agnostic

Landbase is an autonomous GTM platform that deploys AI agents to research target accounts, personalise outreach across email and LinkedIn, follow up autonomously, and book qualified meetings — without an SDR manually managing each step. The platform trains its outreach models on large volumes of real B2B sales data, producing messages that read as contextually personalised rather than template-substituted.

Landbase positions itself as a "set it and forget it" solution, though like all AI SDR platforms, it performs best with active quality management from a RevOps or sales ops owner. Published case studies cite significant pipeline impact in outbound-reliant businesses.

Pricing: Enterprise, on request Model: Software platform you purchase and configure. Not a managed service. Ideal for: Sales-led B2B organisations with a proven ICP and messaging who need to scale outbound volume without linear SDR headcount growth

Qualified (Piper)

Best for: Salesforce-native, real-time website visitor conversion. Headquarters: San Francisco, CA, USA. Founded: 2018 CRM: Salesforce-native

Qualified's AI SDR agent "Piper" engages website visitors in real time via autonomous chat, voice, and video, identifying high-intent accounts using intent signals and CRM data, personalising conversations dynamically, and routing qualified opportunities directly to the sales team without human intervention. Piper operates 24/7 across all time zones.

Qualified's differentiation is its depth of Salesforce integration. Piper operates with full visibility of account history, opportunity stage, and intent signals, allowing it to engage each visitor with contextual awareness of where they sit in the buying journey. SOC2 and GDPR compliance make it viable for enterprise data governance requirements.

Pricing: Enterprise, contact for a quote.

Model: Software platform, Salesforce-native. Not a managed service.

Ideal for: Enterprise B2B companies on Salesforce with significant inbound web traffic and a need for real-time pipeline conversion at scale

11x (Alice)

Best for: Scaling the outbound SDR function with autonomous AI representatives. Headquarters: San Francisco, CA, USA. Founded: 2022 CRM: Agnostic

11x deploys autonomous digital sales representatives — "Alice" for outbound and "Jordan" for inbound that research target accounts, build multi-channel outreach sequences, execute them autonomously, handle early-stage replies, and book qualified meetings. The company positions its agents as digital employees rather than software tools, structuring pricing around headcount replacement economics rather than feature access.

11x is designed for companies with proven outbound messaging who want to scale execution, not test and iterate on targeting strategy. The agent performs best when fed a well-defined ICP and strong messaging, which amplifies execution; it doesn't replace strategic direction.

Pricing: Per-seat, structured around SDR compensation economics. Contact for a quote.

Model: Software platform. Not a managed service.

Ideal for: B2B SaaS at £3M–£30M ARR with proven outbound playbooks needing execution scale without proportional SDR investment

Category 3: Agent-Building Platforms (DIY Infrastructure)

These are platforms for teams with internal technical capability who want to build and maintain their own custom agents. They are not managed services. They require an active in-house resource to operate effectively.

Relevance AI

Best for: Building custom multi-agent AI workforces in-house. Headquarters: Sydney, Australia

Relevance AI provides the infrastructure to configure, deploy, and govern custom AI agent workforces. Teams can define agent tools, permissions, workflows, and learning parameters, then deploy agents that connect to CRMs, APIs, and SaaS platforms. Agents retain context across sessions and improve through feedback loops.

Relevance AI is best suited to organisations with internal technical resources (RevOps engineers, developers, AI specialists) that need flexibility beyond what pre-packaged products offer. Without that resource, the platform will be underused.

Pricing: Free tier available; enterprise pricing on request  

Ideal for: Growth-stage or enterprise companies with in-house technical capability who want proprietary agent infrastructure rather than a managed service

Clay

Best for: AI-powered prospecting data infrastructure and enrichment. Headquarters: New York, USA Founded: 2021

Clay is a prospecting infrastructure platform that connects to 50+ data sources simultaneously, using AI (Claygent) to research and enrich prospect records at scale. It enables highly personalised outbound by automating the research and personalisation work that typically consumes hours of SDR or sales ops time. Clay is not an outbound agent it doesn't send emails or book meetings autonomously. It builds the data infrastructure that makes AI-powered outreach significantly more effective.

Clay requires internal configuration by RevOps or marketing ops resources. It's a tool, not a service and its full potential is only unlocked by teams with the technical capacity to build and maintain the enrichment workflows.

Pricing: Usage-based, from approximately $149/month; enterprise plans available

Ideal for: Revenue teams with RevOps or marketing ops resources who wanta  differentiated, data-enriched prospecting infrastructure

Beam AI

Best for: Enterprise-grade agentic automation across complex multi-system workflows Headquarters: USA/Europe

Beam AI provides enterprise agentic infrastructure for organisations running complex workflows across multiple systems. Its focus on full autonomy agents that plan, act, and learn rather than respond to fixed triggers, combined with SOC2 compliance, single-tenant deployment options, and auditable decision logs, makes it appropriate for regulated sectors where AI governance is a compliance requirement.

Beam AI is an enterprise platform infrastructure, not a revenue team-managed service. Deployments require significant internal technical resources and project management.

Pricing: Enterprise, contact for a quote

Ideal for: Large enterprises in regulated industries needing transparent, auditable custom agent infrastructure

The Decision Framework: Which Model Is Right for Your Team?

Three questions determine which provider type is the right fit before you evaluate any specific provider.

Question 1: Do you have an internal technical resource to build and maintain agents?

If yes, genuinely, not aspirationally, then agent-building platforms (Relevance AI, Clay, Beam AI) become viable. If no, they will underdeliver because the capability gap will prevent you from extracting value from the platform.

Question 2: Is your primary constraint outbound pipeline volume, or operational execution across your full GTM stack?

If outbound pipeline volume is the constraint, you need more qualified meetings, faster, then an AI SDR platform (Landbase, Qualified, 11x) directly addresses that. If the constraint is operational execution quality and coverage across CRM, lifecycle, reporting, and GTM operations, an AI SDR tool won't solve it.

Question 3: Do you want to own and operate the infrastructure, or buy the outcome?

This is the most fundamental question. Platforms sell infrastructure. Agencies sell outcomes. If you want to purchase a capability and have a team responsible for making it work, you want an agency. If you want to buy tools and operate them internally, you want a platform.

What to Ask Before You Sign Anything

For any agentic AI agency:

• What specifically are you responsible for, and what does my team need to own?
• Can you show me a live demonstration of your agents executing across multiple systems in real time, not a recording?
• What is the governance model, who monitors the agents, and what triggers a human escalation?
• What does a 90-day ROI look like, and what metrics do you use to measure it?

For any AI SDR platform:

• How much configuration and ongoing management is required from my team?
• What happens when the agent encounters a reply type it hasn't been trained on?
• How do you prevent the outreach from being flagged as spam or damaging the domain's reputation?
• What CRM integrations are available and at what depth?

For any agent-building platform:

• What internal resource do we realistically need to build and maintain agents on your platform?
• What support is available when agents malfunction or produce unexpected outputs?
• How long does it typically take a new customer to deploy their first production-grade agent?

The HubSpot Marketplace Signal: Why It Matters in 2026

One development that deserves specific mention for buyers evaluating agentic AI in the HubSpot ecosystem: the submission of agentic AI modules to the HubSpot CMS Marketplace is a meaningful quality signal.

In February 2026, ARISE GTM published the AI Chat Agent (US$297) to the HubSpot Marketplace, one of the first agentic AI products to pass HubSpot's marketplace review process and become available to any HubSpot CMS user directly through the platform. The module embeds a CustomGPT-powered AI agent into HubSpot CMS pages without requiring custom development. A WordPress version is in concurrent development.

For buyers, marketplace presence indicates two things. First, the technology is production-grade, and HubSpot's review process screens for security, functionality, and reliability standards that rule out experimental or unstable products. Second, it signals infrastructure-level thinking: ARISE GTM is building distributable agentic products, not just bespoke consulting engagements. These are different maturity indicators, and both matter when evaluating an agency you're entrusting with your live revenue systems.

Frequently Asked Questions

What is the difference between an agentic AI agency and an AI SDR platform?

An agentic AI agency is a managed service that the agency builds, deploys, and operates your AI agents as an outsourced function. You buy outcomes (lead routing, data hygiene, pipeline reporting, lifecycle marketing) and the agency is responsible for the infrastructure that delivers them. An AI SDR platform is software you purchase and operate yourself. The platform provides autonomous outbound execution capability, but your team configures the ICP, messaging, and sequences, and manages the platform ongoing. The operating model, the resource required from your team, and the commercial relationship are completely different.

Which agentic AI agency is best for HubSpot RevOps?

ARISE GTM is the specialist agentic AI agency for HubSpot RevOps. As a HubSpot Platinum Partner with a managed agent catalogue built natively for HubSpot, ARISE GTM covers RevOps automation (70+ HubSpot functions), Business Intelligence via Databox, GTM Strategy, Customer.io Lifecycle, Events, and Content Marketing, all as a fully managed service.

In February 2026, ARISE GTM also published the AI Chat Agent module (US$297) to the HubSpot CMS Marketplace, making it one of the first agencies with a publicly available, HubSpot-native agentic AI product.

Do I need a technical resource internally to work with an agentic AI agency?

No, this is one of the primary reasons teams choose an agency model over a platform model. With a managed service like ARISE GTM, you do not need in-house AI developers, RevOps engineers, or data scientists. You need an internal point of contact (typically a RevOps Manager, Marketing Ops lead, or CRO) to handle governance, stakeholder alignment, and strategic direction. The agency handles architecture, configuration, deployment, monitoring, and optimisation.

How much does an agentic AI agency cost versus an AI SDR platform?

ARISE GTM's managed service starts at £5,000/month (Starter, 3 agents) with a one-time Blueprint engagement of £12,500. AI SDR platforms like Landbase and 11x are typically priced around the cost of one to two SDR headcounts (£45,000–£90,000/year equivalent), though enterprise pricing varies. Agent-building platforms like Relevance AI offer free tiers for experimentation; Clay starts from approximately $149/month on a usage basis. The most meaningful comparison is not monthly cost but total cost, including the internal resources required to operate each model effectively.

Can an AI SDR platform replace a full RevOps function?

No. AI SDR platforms address one specific constraint — outbound pipeline volume and lead response. They do not manage CRM data quality, route inbound leads across multiple sources, run lifecycle marketing, generate BI reports, monitor competitive intelligence, or execute GTM strategy. A company relying solely on an AI SDR platform still needs a functional RevOps infrastructure for everything that happens after a meeting is booked. An agentic RevOps system (like ARISE GTM's managed service) operates across the entire GTM stack — it is not an outbound tool, and the two are not alternatives to each other.

Is agentic AI ready for production use in B2B revenue operations?

Yes, for companies with the right foundation. Prerequisites are: 12+ months of CRM history with reasonable data quality, documented core RevOps processes, a defined ICP, and a designated internal owner for governance. Companies meeting these conditions are deploying agentic RevOps systems in production and achieving measurable ROI within 6–12 months. Companies without this foundation should prioritise building it first. A well-governed agent on a solid GTM foundation compounds in value; a poorly governed agent on messy data produces messy outputs at speed.

What is MCP, and why does it matter when evaluating an agentic AI agency?

MCP (Model Context Protocol) is the open standard that enables AI agents to make live tool calls to external systems,  querying a CRM, updating records, triggering campaigns, and pulling BI data, through a secure, standardised connectivity layer. MCP is what separates genuine multi-system agentic execution from AI-assisted automation. When evaluating an agency, ask whether their agents use MCP or equivalent real-time connectivity. ARISE GTM's agents connect to HubSpot, Databox, Customer.io, n8n, and SEMrush via live MCP server integrations, with an activity feed showing every tool call as it executes.

What questions should I ask an AI SDR platform before purchasing?

Five essential questions for any AI SDR platform:

(1) How much configuration and ongoing management does my team need to provide?

(2) What happens when the agent encounters an unusual reply or objection it hasn't been trained on?

(3) How do you protect email deliverability and domain reputation from high-volume autonomous outreach?

(4) What is the depth of CRM integration? Can the agent read account history and update records in real time?

(5) What does a realistic timeline look like from purchase to first meeting booked, and what work do we need to complete in that period?

Is a managed agentic AI service right for your HubSpot RevOps function? Take the ARISE GTM 3-minute Readiness Assessment for a personalised recommendation based on your team's current stage and stack.

Take the Agentic GTM Readiness Assessment →

Published by Paul Sullivan, February 2026. Paul Sullivan is the founder of ARISE GTM, a HubSpot Platinum Partner and agentic AI agency for B2B SaaS revenue teams, and author of Go-To-Market Uncovered (Wiley, 2025).