Institutional memory for go-to-market agents.
Institutional memory for go-to-market agents.
Institutional memory for go-to-market agents.
Build your revenue engine on a context layer that learns how your company wins deals.
Build your revenue engine on a context layer that learns how your company wins deals.
Your agents have data.
They do not have context.
Your agents have data.
They do not have context.
01
01
Data
Data
When your agents start from raw records, they have to rebuild revenue context from scratch. Political risk is missed, the wrong buyer looks like the champion, and the same signals are interpreted differently every time.
When your agents start from raw records, they have to rebuild revenue context from scratch. Political risk is missed, the wrong buyer looks like the champion, and the same signals are interpreted differently every time.
02
02
Context
Context
When the data is pre-processed into a unified context layer, your agents wake up to the same revenue reality. Every downstream judgment is grounded in what changed, what matters now, and what has worked before.
When the data is pre-processed into a unified context layer, your agents wake up to the same revenue reality. Every downstream judgment is grounded in what changed, what matters now, and what has worked before.
Context that compounds
with every outcome.
Context that compounds
with every outcome.
01
01
Model
Model
Everboard learns the hidden patterns that predict how your deals unfold.
Everboard learns the hidden patterns that predict how your deals unfold.
> Running temporal analysis...
> Running temporal analysis...
- internal_politics_risk: increasing steadily
- internal_politics_risk: increasing steadily
- champion_likelihood (Anna K): weakening
- champion_likelihood (Anna K): weakening
- multithreading_strength: still weak
- multithreading_strength: still weak
> Running predictive model...
> Running predictive model...
- p_progression_60d: 32.4% (vs. 38.9% baseline)
- p_progression_60d: 32.4% (vs. 38.9% baseline)
- confidence: moderate
- confidence: moderate
02
02
Context
Context
Ground agent reasoning in the winning patterns behind relevant deals.
Ground agent reasoning in the winning patterns behind relevant deals.
> Retrieving relevant paths...
> Retrieving relevant paths...
- matches: 22
- matches: 22
- target_dimensions: multithreading_strength, internal_politics_risk
- target_dimensions: multithreading_strength, internal_politics_risk
- missing_actions: thread_economic_buyer, coauthor_business_case
- missing_actions: thread_economic_buyer, coauthor_business_case
> Recommending next moves...
> Recommending next moves...
- Create direct access to Damien H before finance gets involved
- Create direct access to Damien H before finance gets involved
- Co-author business case with Priya M and Anna K
- Co-author business case with Priya M and Anna K
04
04
Outcome
Outcome
Every win, loss, and stall feeds back into your company’s unique model.
Every win, loss, and stall feeds back into your company’s unique model.
> Observing outcome...
> Observing outcome...
> Observing outcome...
- inferred_stage: proposal
- inferred_stage: proposal
- inferred_stage: proposal
- result: stall
- result: stall
- result: stall
> Updating context...
> Updating context...
> Updating context...
- champion_likelihood (Anna K): low → very low
- champion_likelihood (Anna K): low → very low
- champion_likelihood (Anna K): low → very low
- p_recovery_60d: 18.7%
- p_recovery_60d: 18.7%
- p_recovery_60d: 18.7%
- missing_actions: thread_economic_buyer
- missing_actions: thread_economic_buyer
- missing_actions: thread_economic_buyer
03
03
Action
Action
Turn agent judgment into consistent seller execution across every deal.
Turn agent judgment into consistent seller execution across every deal.
> Observing actions...
> Observing actions...
- seller: Matt B
- seller: Matt B
- window: 28 days
- window: 28 days
> Processing evidence...
> Processing evidence...
- sources: 3 meetings, 2 transcripts, 7 emails
- sources: 3 meetings, 2 transcripts, 7 emails
- completed_actions: coauthor_business_case
- completed_actions: coauthor_business_case
- missing_actions: thread_economic_buyer
- missing_actions: thread_economic_buyer
One layer.
Every agent.
One layer.
Every agent.
01
01
Connect your systems
Connect your systems
Everboard maintains a unified context layer above your revenue stack.
Everboard maintains a unified context layer above your revenue stack.
02
02
Connect your agents
Connect your agents
Everboard provides revenue context to every agent, wherever they run.
Everboard provides revenue context to every agent, wherever they run.
FAQs
FAQs
> What data does Everboard ingest?
> What data does Everboard ingest?
CRM records, calendars, emails, call notes and transcripts. All the raw activity data already flowing through your systems.
CRM records, calendars, emails, call notes and transcripts. All the raw activity data already flowing through your systems.
> How long before the context is useful?
> How long before the context is useful?
Everboard processes all your historical data on day one. Context on your live pipeline is immediately useful.
Everboard processes all your historical data on day one. Context on your live pipeline is immediately useful.
> How does your predictive model work?
> How does your predictive model work?
Everboard trains a company-specific ML model on your historical deal patterns to predict wins, stalls, and losses.
Everboard trains a company-specific ML model on your historical deal patterns to predict wins, stalls, and losses.
> How is my data stored and protected?
> How is my data stored and protected?
Everboard is built securely on SOC 2 Type II and ISO 27001 certified providers. Data is encrypted in transit and at rest.
Everboard is built securely on SOC 2 Type II and ISO 27001 certified providers. Data is encrypted in transit and at rest.
> How do my agents access the context?
> How do my agents access the context?
Via our REST API or MCP server. Connect to Everboard using standard protocols from any agent platform or surface.
Via our REST API or MCP server. Connect to Everboard using standard protocols from any agent platform or surface.
> Do you train a universal model on my data?
> Do you train a universal model on my data?
No. Your data is isolated and we have zero-retention agreements with model providers.
No. Your data is isolated and we have zero-retention agreements with model providers.
Build GTM agents that learn from your wins and losses.
Build GTM agents that learn from your wins and losses.
© Everboard Inc.