Account intelligence written for humans — structured for AI
Accoil generates privacy-aware, plain-language summaries that explain what is happening in every account and why. Designed as structured narratives that humans read and AI agents reason over — so every system that touches your customers has real context.
The engagement context layer for your entire stack.
Your accounts have a story. Nobody has time to read the raw data.
An account scores 23. Another scores 95. The numbers tell you something is different — but not what happened, when it changed, or what to do about it. Teams dig through event streams and dashboards trying to reconstruct the narrative. AI support agents and sales copilots operate with zero context about who they are talking to. AI Summaries solve both problems at once. Accoil continuously generates concise, structured narratives that explain account health, momentum, and risk — written so a CSM can scan them before a call, and formatted so an AI agent can reason over them in real time. One summary. Two audiences. No PII leaves your environment.
- A score-23 account gets a summary explaining the drop: which features went quiet, when usage declined, and what segment the account moved into — not just a number, but the full story behind it.
- Every AI tool in your stack — support bots, sales copilots, internal agents — can consume the same structured context via API, instantly.
- No more manual account reviews. No more guesswork about what caused a score to move. Consistent, actionable narratives that update as behaviour changes.
Key capabilities
Dual-Consumption Summaries
Every summary is a structured narrative optimised for two audiences simultaneously. Humans get clear, scannable prose. AI agents and LLMs get consistent, well-formatted context they can parse, reference, and act on. One output serves your entire stack — from a CSM reading before a call to an Intercom Fin agent triaging a support ticket.
Score-to-Story Translation
Engagement scores quantify health. Summaries explain it. When an account drops from 72 to 34, the summary surfaces what changed — which features went silent, which users disengaged, and how the trajectory compares to accounts that churned. The score tells you to act. The summary tells you how.
Privacy-Aware AI Generation
Summaries are generated without sharing account names, user identities, or personal data with external LLMs. Accoil's AI engine works with anonymised, structured engagement data — delivering rich narrative context while keeping sensitive information inside your environment.
How it works
Accoil structures your engagement data
Scores, segments, events, activation progress, trends, and traits are organised into a structured representation of each account — the raw material for narrative generation.
The AI engine identifies what matters
Changes in engagement, segment movements, feature adoption shifts, risk signals, and expansion indicators are detected and prioritised. The engine determines what is worth surfacing — not just what changed, but what is significant.
Structured summaries are generated and delivered
A concise, privacy-aware narrative is produced for each account — explaining health, momentum, risk, and opportunity in a format that humans can read and AI agents can consume via API. Summaries update continuously as new behaviour arrives.
No prompt engineering required. No dashboard configuration. Summaries are generated automatically and delivered wherever your teams and AI tools need them.
Integrations & actions
AI Summaries surface directly inside the tools your team already uses — giving every customer-facing touchpoint the engagement story behind the score.
Intercom
Account summaries appear alongside support conversations. Before a rep or AI agent responds, the engagement narrative is already there — what the account has been doing, what changed, and what it means. Context without switching tools.
HubSpot
Summaries push to HubSpot account records so sales and CS teams see the full engagement story in their CRM. Reps prep for calls with real context, not stale field values.
Jira Service Management
Account summaries surface in JSM so support teams handling service requests see engagement context alongside the ticket. Prioritise and route with awareness of account health.
What this unlocks
For customer success
- Read a summary before any call — know the full engagement story, not just the score
- Identify exactly what changed when an account moves to at-risk, so outreach is specific
- Use summary context to tailor guidance — recommend the features the account has stopped using, not generic advice
For product teams
- See narrative explanations of how accounts engage with specific features across segments
- Spot patterns in what drives accounts from activation to healthy engagement
- Feed summary context into internal AI tools that surface product insights at scale
For sales & revenue
- AI sales copilots receive structured context about expansion-ready accounts, including which features are driving engagement
- Understand the momentum behind a score-95 account — what they adopted, how usage is trending, and who the champions are
- Time expansion conversations around real engagement inflection points surfaced in summaries
For leadership
- Quick, objective account narratives before board prep or investor meetings — no dashboard archaeology
- AI-generated portfolio health overviews that explain trends, not just chart them
- Consistent, structured account intelligence that feeds into strategic AI tooling
Give every system in your stack real account context
AI Summaries turn engagement data into structured narratives that humans scan and AI agents reason over. Start seeing the story behind every score.
- Privacy-aware AI — no PII shared with external LLMs
- Structured for human and AI consumption
- Continuous updates as behaviour changes