The context layer for revenue agents.
Everboard turns your raw GTM data into deep customer understanding. Give agents the context and memory they need to execute reliably across
your revenue stack.
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You’re shipping agents on fragmented systems of record. What they need is a connected system of understanding.
Scenario: Where do my reps need coaching?
Scenario: Which prospects can I reengage?
Scenario: Why are we really losing deals?
Level 1: Workflow
Generic output based off a single call. No account or rep context to deliver meaningful coaching insights.
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The prospect asked detailed onboarding questions. Coach the rep on creating urgency around implementation with Ops.
Latest Transcript
Level 2: Agent + data
Narrow interpretation of deal risk and progression. Coaching not grounded in precedent from similar deals.
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Acme is in the proposal stage. Over the last two calls, most of the discussion centered around onboarding timelines and internal resourcing with no clear owner identified on the buyer’s side. Encourage the rep to bring in Ops and confirm who will own rollout.
3 transcripts
CRM records
CRM activities
Level 3: Agent + understanding
Nuanced deal strategy built on causal understanding of the account, rep, and historical win-loss patterns.
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Acme’s real risk isn’t implementation. The COO drove urgency early on but dodged pricing conversations, and the champion hasn’t brought in other stakeholders. In similar proposal-stage losses, you mistook diligence for momentum and failed to secure exec buy-in on value. Reengage the COO, widen Ops support, and tighten the business case before discussing features.
Stakeholder coverage
Business case strength
Win-loss patterns by stage
Rep growth areas
We don’t replace your agents.
We give them structured context and memory to work with.
Step 1
Connect your GTM data.
We continuously extract signals and build a connected understanding of every account, deal, and stakeholder.
Step 2
Define repeatable tasks.
Your agents execute custom instructions safely and reliably with full operational context and memory.
Step 3
Put your data to work.
Plug task outputs back into your workflows to deliver useful work across your existing revenue stack.
FAQ.
1/ Can’t I just get my agents to work with the data I have?
You should always steer your agents on data handling but this doesn’t change the quality of the data itself. Everboard gives agents a stable, structured view of the customer so they don’t need to reinterpret one from raw facts every time. This improves quality and consistency, slashes token costs, and gives you a durable model of customer understanding you can leverage as an organizational asset.
2/ Why can’t I just use my agent builder’s search tools?
This gives the model more places to look for information, but doesn't automatically give it more understanding. Sometimes a well prompted agent can piece everything together into a nuanced, coherent narrative that’s properly evidenced by its source data, but not efficiently or reliably enough to scale in production.
3/ Can’t I just use the agents inside my point solutions?
Only if you need agents to perform narrow tasks on thin slices of data. More capable agents need wider customer understanding to exercise good judgment, which can only be developed by making connections across your entire GTM stack.
4/ How do I make sure my agents don’t do anything stupid?
You control what data your agents can and can’t see, and decide how outputs are routed downstream. Everboard is a pluggable context layer for your agents, not a black box replacement for your workflows.
5/ How is my data stored and protected?
Everboard is secure by design and runs on cloud services from SOC 2 Type II and ISO 27001 certified providers, with data encrypted in transit and at rest.
6/ Do you train a model on my data?
No. We don’t share your data for model training purposes.
Plug-in revenue intelligence for your agent workforce.
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