The context layer for revenue agents.
The context layer for revenue agents.
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.
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.
> Get early access
You’re shipping agents on fragmented systems of record.
What they need is a connected system of understanding.
You’re shipping agents on fragmented systems of record.
What they need is a connected system of understanding.
"Where do my reps need coaching?"
"Which prospects can I reengage?"
"Why are we really losing deals?"
Level 1: Workflow
Generic analysis of a single call. No context on the deal or rep to deliver meaningful coaching value.
>
The prospect asked detailed onboarding questions. Coach the rep on creating urgency around implementation with Ops.
Latest Transcript
Level 2: Agent + data
Basic insights on deal risk and progression. Coaching not grounded in precedent from successful outcomes.
>
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 activity
Level 3: Agent + understanding
Deal strategy built on causal understanding of the account, the rep, and historical win-loss patterns.
>
Acme’s real risk isn’t implementation. The COO drove urgency early on but dodged pricing discussions, and the champion hasn’t brought in other stakeholders. In past 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
"Where do my reps need coaching?"
"Which prospects can I reengage?"
"Why are we really losing deals?"
Level 1: Workflow
Generic analysis of a single call. No context on the deal or rep to deliver meaningful coaching value.
>
The prospect asked detailed onboarding questions. Coach the rep on creating urgency around implementation with Ops.
Latest Transcript
Level 2: Agent + data
Basic insights on deal risk and progression. Coaching not grounded in precedent from successful outcomes.
>
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 activity
Level 3: Agent + understanding
Deal strategy built on causal understanding of the account, the rep, and historical win-loss patterns.
>
Acme’s real risk isn’t implementation. The COO drove urgency early on but dodged pricing discussions, and the champion hasn’t brought in other stakeholders. In past 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
"Where do my reps need coaching?"
"Which prospects can I reengage?"
"Why are we really losing deals?"
Level 1: Workflow
Generic analysis of a single call. No context on the deal or rep to deliver meaningful coaching value.
>
The prospect asked detailed onboarding questions. Coach the rep on creating urgency around implementation with Ops.
Latest Transcript
Level 2: Agent + data
Basic insights on deal risk and progression. Coaching not grounded in precedent from successful outcomes.
>
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 activity
Level 3: Agent + understanding
Deal strategy built on causal understanding of the account, the rep, and historical win-loss patterns.
>
Acme’s real risk isn’t implementation. The COO drove urgency early on but dodged pricing discussions, and the champion hasn’t brought in other stakeholders. In past 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.
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, stakeholder, and rep.
Step 2
Define repeatable skills.
Your agents execute custom instructions safely and reliably with full operational context and memory.
Step 3
Put your data to work.
Plug outputs back into your workflows to deliver useful work across your existing revenue stack.
Step 1
Connect your GTM data.
We continuously extract signals and build a connected understanding of every account, stakeholder, and rep.
Step 2
Define repeatable skills.
Your agents execute custom instructions safely and reliably with full operational context and memory.
Step 3
Put your data to work.
Plug outputs back into your workflows to deliver useful work across your existing revenue stack.
FAQ.
FAQ.
1/ Can’t I just connect data sources directly to my agent?
1/ Can’t I just connect data sources directly to my agent?
Raw GTM data is noisy and fragmented. Giving an agent more places to look for information does not automatically give it understanding. When forced to reinterpret the state of the world every time, the model will compress and guess. This makes your agents unreliable across runs, and your system unreliable across agents.
Raw GTM data is noisy and fragmented. Giving an agent more places to look for information does not automatically give it understanding. When forced to reinterpret the state of the world every time, the model will compress and guess. This makes your agents unreliable across runs, and your system unreliable across agents.
2/ Why is Everboard’s context that much better?
2/ Why is Everboard’s context that much better?
Everboard continuously ingests, cleans, and reconciles your raw data, interprets its meaning, and maintains a long-term, structured memory of your revenue org that compounds over time. This improves the quality and consistency of your agents, slashes token costs, and gives you a durable model of customer understanding you can leverage as an organizational asset.
Everboard continuously ingests, cleans, and reconciles your raw data, interprets its meaning, and maintains a long-term, structured memory of your revenue org that compounds over time. This improves the quality and consistency of your agents, slashes token costs, and gives you a durable model of customer understanding you can leverage as an organizational asset.
3/ Can’t I just use the agents inside my point solutions?
3/ Can’t I just use the agents inside my point solutions?
Only if you need agents that perform narrow tasks on thin slices of data. More capable agents need wider customer understanding to exercise good judgment, which is only developed by making connections across your GTM stack.
Only if you need agents that perform narrow tasks on thin slices of data. More capable agents need wider customer understanding to exercise good judgment, which is only developed by making connections across your GTM stack.
4/ How do I make sure my agents don’t do anything stupid?
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.
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?
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.
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?
6/ Do you train a model on my data?
No. We don’t share your data with other users or with model providers for training purposes.
No. We don’t share your data with other users or with model providers for training purposes.
Plug-in revenue intelligence for your agent workforce.
What will you ship today?
Plug-in revenue intelligence for your agent workforce.
What will you ship today?
> Get early access
© Everboard Inc.