Account research agents
Pull company context, buying triggers, role maps, and relevant proof points before a seller opens a call or writes outreach.
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B2B Sales
AI Agents for B2B Sales Teams
Your best sellers should not be trapped inside CRM maintenance.
Direct answer
AI agents for B2B sales teams
Arkhos Labs builds custom AI agents for B2B sales teams that research accounts, prepare outreach, update CRM records, draft follow-up, and keep pipeline operations moving without turning sellers into prompt engineers.
Use cases
Workflows we can own
Follow-up and handoff agents
Turn call notes into recap emails, next steps, CRM updates, and internal handoffs while the conversation is still fresh.
Pipeline hygiene agents
Detect stale opportunities, missing fields, duplicate records, and mismatched next steps before forecast calls.
Systems
Integrations the agent has to respect
SalesforceHubSpotApolloClayGongSlackGoogle WorkspaceMicrosoft 365
Controls
Where the implementation has to be careful
Seller approval for outbound
The system drafts research-backed messages and sequences, but sellers approve what goes to buyers.
CRM writes with guardrails
Agents can suggest or queue record updates before making changes to forecast-critical fields.
Brand-safe personalization
Outreach uses approved positioning and real account signals instead of generic personalization filler.
The hidden cost of sales tool sprawl
Most sales teams already have enough software. The problem is that sellers still move data between tools by hand, rebuild account context from scratch, and leave follow-up trapped in meeting notes.
That is not selling. It is operational drag.
What we build for sales teams
Research agents
Before outreach or a call, the agent builds an account brief from CRM, company data, public signals, call history, and your approved positioning.
Follow-up agents
After a call, the agent drafts the recap, updates the opportunity, captures next steps, and routes internal tasks to customer success, solutions, or leadership.
Pipeline agents
The agent watches CRM quality, stale opportunities, missing close plans, and forecast gaps so managers see issues before the weekly pipeline meeting.
Built for revenue teams with standards
- Approved messaging. The system uses your positioning, proof points, and disallowed claims.
- Forecast hygiene. Agents can queue CRM changes for review before touching sensitive fields.
- Rep adoption. The work shows up where sellers already live, not inside a separate AI toy.
Engagement model
- Week 1-2. Map sales stages, CRM rules, call flow, and outbound standards.
- Week 3-6. Build one research or follow-up agent against live sales scenarios.
- Week 7-8. Run alongside sellers and compare time saved, completion rate, and CRM quality.
- Week 9+. Expand into enrichment, renewal, customer handoff, and forecast workflows.
Book a call. Bring one sales motion that depends on too much manual follow-up, and we will map the agent.
Questions
Answers buyers usually need first
What can AI agents do for B2B sales teams?
AI agents can research accounts, enrich contacts, draft outbound, summarize calls, update CRM records, route follow-up, and identify pipeline hygiene issues.
Is this the same as a sales engagement platform?
No. A custom sales agent works across the systems your team already uses and can follow your sales process instead of forcing a generic workflow.
Where should a sales team start?
Start with account research and post-call follow-up because both are high-volume, easy to measure, and painful for sellers.
Proof points
- Built for sales teams that have tools but still lose time in manual handoffs.
- Designed to improve sales execution without creating unapproved buyer messaging.
- Strong fit for teams with clear ICP, call notes, CRM standards, and outbound playbooks.
Related pages
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