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Vendor review · Per-account agents · $45M Series B (Apr 2026)

Actively AI Review: Per-Account Agents That Replace the SDR Research Stack

Actively AI raised $45M Series B on April 28, 2026 (TCV-led, $68M total) to scale per-account AI agents — one dedicated agent per account, working 24/7, doing the research and next-action work the SDR + AE team can't sustain manually. The headline customer is Samsara (1,000+ GTM team, claimed 2x conversion lift). The replacement claim: agents that eliminate the SDR research workflow that today lives across Common Room, Clay, and manual ZoomInfo/Apollo/LinkedIn searching. Operator-grade read on what it actually does, what it actually replaces, and when to evaluate vs wait.

By Nick French · Founder, StackSwap · 10yrs B2B SaaS GTM (BDR → AE → Head of Revenue) · Methodology →
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What Actively AI actually does

Per their own positioning: "Per-Account Agents work every account 24/7, guide your team on what to do next, and help them do it." Concretely, the agent runs five workflows per account, continuously:

  • Account research: Pulls firmographics, tech stack, recent news, hiring signals, executive moves.
  • Signal monitoring: Watches the account for buying signals, organizational changes, intent data, competitive moves.
  • Outreach drafting: Generates personalized outbound based on the research and signals — sequencer-ready copy with the context baked in.
  • Deal-risk surfacing: Flags stalling deals, missing stakeholders, competitive threats. Drafts the next action.
  • Next-action recommendation: Tells the rep what to do next on each account, with the supporting context.

The framing matters: Actively isn't selling a research dashboard or a signal monitoring tool or a sequencer. It's selling an autonomous worker that does what today gets distributed across an SDR team using 5-7 different tools.

What it replaces in your stack

Five common line items in a typical SDR research stack and how Actively AI relates to each:

IncumbentFunctionOverlapCut, keep, or hybrid
Common RoomBuyer + account signal monitoringHighCommon Room watches signals (job changes, GitHub activity, community engagement). Actively AI agents do this per-account continuously and act on what they find.
ClayEnrichment + research workflow orchestrationMedium-HighClay is the workflow layer for enrichment chains. Actively AI bundles equivalent enrichment into the per-account agent — but Clay still wins for one-off custom workflows.
Apollo + ZoomInfo manual researchSDR account/contact researchHighThe agent uses these data sources but eliminates the SDR manual research workflow. You probably still need ZoomInfo or Apollo as the underlying data layer.
Custom-built SDR research playbooks (Notion + Airtable + Slack)Account research documentation + handoffHighThe agent generates the same research artifacts (account briefs, ICP fit notes, signal summaries) without the documentation tax.
Outreach/Salesloft AI features (Outreach AI, Rhythm)Sequence personalization + next-action recommendationsMediumVendor-native AI features overlap on the personalization layer but not on the per-account research depth. Most teams will need both for now.

Pricing reality

No public pricing. Demo-gated. Based on the customer profile (Samsara at 1,000+ reps, Ramp at scale, enterprise positioning) and the per-account business model, the entry point is almost certainly six figures annually. Per-account pricing scales aggressively with TAM expansion — if you have 5,000 named accounts, the per-account math compounds.

The honest evaluation framework: don't look at Actively's sticker price in isolation. Sum the line items it would replace (Common Room subscription, Clay seats, ZoomInfo seats for non-prospecting roles you'd reclaim, custom research workflow time) and compare. For most enterprise teams, the math works only if you actually cut the incumbents.

When to evaluate vs when to wait

Five team profiles and the fit verdict for each:

Team profileFitWhy
30+ rep SDR/BDR team running outboundStrongPer-account agent productivity gains scale with rep count. Samsara case study: 1,000+ GTM team, 2x conversion on Actively-driven outreach.
Enterprise AE org managing 50-200 named accounts eachStrongPer-account model fits the named-account motion. AEs get a research agent dedicated to each account in their book.
PLG team with primarily inbound motionWeakPer-account research is less valuable when leads come in pre-qualified. Look at inbound-conversion agents (Intercom Fin for Sales) instead.
Sub-30-rep startupWeakPricing is enterprise-tier ("request a demo"). The unit economics likely don't justify it below $5M ARR.
Team already on Common Room + Clay + custom research stackStrong evaluation candidateYou're paying for the components that Actively bundles. The replacement math is the most favorable here.

Customer proof — what we know

Two named customers in the public press release: Samsara (Robert Stobagh, COO - GTM) and Ramp (Michael Manne, VP of Sales). Three additional customer quotes attributed to VPs at unnamed companies. The Samsara claims:

  • 1,000+ person GTM team with Actively agents deployed
  • Spans account development, sales, RevOps, customer success
  • 2x conversion rates on Actively-driven sales outreach
  • Improved quota attainment among top-half sellers
  • "Saved millions in compute and token costs" while accelerating AI roadmap

These claims come from Actively's own press release. They're plausible given the customer profile and per-account model, but we haven't independently verified the 2x conversion lift. Treat as directional, not gospel.

The agent-shaped redundancy risk

The most predictable failure mode for Actively AI adopters: keep Common Room, keep Clay, keep the manual research workflow "during transition," and end up paying for everything. 12-18 months later, total spend has compounded instead of consolidated.

The fix: before signing the Actively contract, set the cancellation deadlines for the incumbents (Common Room, Clay) aligned to next-renewal windows. Build the migration plan during the Actively pilot. Treat the incumbent contracts as on-the-clock the moment Actively gets adopted.

Sources

FAQ

Actively AI is a per-account AI agent platform for revenue teams. The pitch: deploy one dedicated agent per account that researches the buyer, monitors signals, drafts outreach, surfaces deal risks, and progresses opportunities — 24/7, autonomously. Founded 2023, $68M total funding ($45M Series B announced April 28, 2026, led by TCV with First Harmonic, Bain Capital Ventures, First Round Capital, Alkeon).

The SDR research stack: Common Room (signal monitoring), Clay (enrichment workflows), and the manual Apollo/ZoomInfo/LinkedIn account-research process. The agent generates the same research artifacts (account briefs, ICP fit notes, signal summaries) without the SDR doing the documentation work. You probably still need ZoomInfo or Apollo as the underlying data layer — the agent uses those sources but doesn't replace them.

Pricing isn't published — it's quoted after a demo. Based on the customer profile (enterprise, 1,000+ rep deployments) and per-account pricing model, the entry point is likely six figures annually. The unit economics question is critical: per-account pricing scales aggressively with TAM expansion. Compare against the line items it replaces (Common Room, Clay, manual research time) to underwrite the math.

Enterprise revenue teams: CROs, Account Executives managing named-account books, SDR/BDR teams running outbound, RevOps leaders responsible for productivity gains. Customer logos include Samsara (1,000+ person GTM team) and Ramp. Best fit: 30+ rep teams with a named-account or outbound-led motion. Weak fit: PLG/inbound-led teams or sub-30-rep startups.

Common Room is signal monitoring (warm signals across community, GitHub, job changes). Clay is enrichment workflow orchestration (you build the chains). Actively AI is autonomous per-account execution — the agent does the research, signal interpretation, and next-action drafting on its own, per account, continuously. The category framing matters: Common Room and Clay are tools your reps use; Actively AI is an agent that does the work for them.

Agent-shaped redundancy. The most predictable failure mode: a team adopts Actively AI but keeps Common Room and Clay on annual contracts because "we still need them during transition." 12-18 months later, the team is paying for all three. The fix: at every renewal cycle, evaluate whether Actively AI has replaced enough of the workflow to cancel the incumbent. Don't adopt the agent without a cutover deadline for the incumbent.

Samsara is the headline customer: 1,000+ person GTM team, 2x conversion rates on Actively-driven outreach, accelerated AI roadmap, "saved millions in compute and token costs." That's the upper bound — Samsara is a public, IPO'd company with massive scale and dedicated AI/RevOps teams. Sub-Fortune 500 deployments will see different numbers. The 2x conversion claim is in the press release; we haven't verified it independently.

Wait if: you're sub-30 reps, primarily inbound, or running an experimental new motion that's still finding product-market fit. Evaluate now if: you're 30+ reps, named-account-led, currently spending $50K+/yr on Common Room + Clay + custom research workflows, and your renewal date is within the next 6 months. The evaluation should be staged (pilot → parallel → cutover) over ~12 months — see the timing playbook on the AI-agents thesis page.

StackSwap doesn't sell agents — we model GTM stacks against 100,000 synthetic stacks and surface which line items are redundant. For Actively AI specifically: if your stack contains Common Room + Clay + dedicated SDR research time, our overlap engine flags those as candidates Actively AI could replace. Run StackScan to see the modeled annual recoverable spend — free; drop your email to unlock the full plan.

Related reading

Canonical URL: https://stackswap.ai/actively-ai-review. Disclosure: StackSwap has no commercial relationship with Actively AI. Sourced from publicly available press releases, vendor website, and third-party coverage as cited above.