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
Shallow 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 on 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
Exec engagement trends
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 steer my existing agents the way I want?
You can and should give your agents custom instructions, but you’re still throwing raw data at them and expecting a consistent world view to materialize on every run. As well as chewing through tokens, this does not create a durable model of customer understanding that evolves over time.
2/ Why aren’t my agent builder’s search tools enough?
This gives the model more places to look for fragmented information. It can sometimes piece it all together into a coherent narrative that’s fully attributed to its source data, but not reliably or efficiently enough to scale in production.
3/ Why not deploy agents inside my point solutions?
Point solutions are deliberately narrow and operate on thin slices of data. Deep customer understanding is 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 with anyone else for model training purposes.
Pluggable revenue intelligence for agent builders. What will you ship today?
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