Your AI agents are making customer decisions without knowing what customers actually do
Intercom Fin triages tickets. Atlassian Rovo prepares meeting briefs. Zendesk AI drafts responses. Custom GPTs route workflows. They all have the same blind spot — zero product usage context. Accoil fixes that. One API call delivers engagement scores, risk signals, usage trends, and AI-ready summaries to any agent, in structured JSON, updated continuously.
No other engagement tool provides this. Not Gainsight. Not Amplitude. Not Intercom's own analytics. This is what they're all missing.
AI agents without engagement context make bad decisions
Every B2B SaaS company is deploying AI agents — in support, in sales, in internal ops. These agents triage tickets, draft responses, prepare renewal briefs, and prioritise outreach. They're fast, available, and scaling. But the context they work from is dangerously thin: plan type, MRR, maybe a stale health field someone updated last quarter. Here's what that looks like. A support ticket comes in: "Having trouble with the export feature." Intercom Fin sees a paying customer on the Growth plan and drafts a standard troubleshooting response. But that ticket is from a score-23 account that dropped 40 points in two weeks, hasn't logged in for 11 days, and has one remaining active user out of a team of twelve. This isn't a feature question — it's a churn signal. Without engagement context, the AI agent can't tell the difference. With Accoil, it can. The same agent sees the score, the trend, the usage collapse, and the AI summary explaining exactly what changed — and escalates immediately. That's the gap AI Context closes.
- AI agents are already making customer-facing decisions — the question is whether they have real data or guesswork
- A score-23 account and a score-95 account sending the same support ticket are two completely different situations — only engagement context reveals that
- No other tool delivers structured, AI-consumable product usage intelligence to external agents — this is Accoil's territory alone
- Privacy-aware by design — engagement scores, segments, and summaries flow to AI agents, never PII or raw behavioural data
Key capabilities
Structured account context via single API call
One REST API call returns the full engagement profile for any account or user — score (0-100), score delta and trend direction, active users, segment membership, activation status, feature adoption depth, risk signals, and an AI-generated summary. Structured JSON, designed for machine consumption. No parsing HTML. No scraping dashboards. No building a data pipeline. Your AI agent gets everything it needs in one request.
AI-ready summaries built for LLM reasoning
Accoil generates plain-language account summaries specifically designed to be consumed by other AI systems. Each summary explains what an account is doing, what changed recently, and what that change means — in a format LLMs can reason over directly. When Intercom Fin or a custom LangChain agent receives this summary alongside a ticket, it has genuine account understanding, not just metadata fields. These summaries update continuously as usage patterns shift.
REST API for any AI tool or agent framework
Accoil's REST API exposes engagement data to any AI tool or agent framework. AI tools query account context with a single API call — returning live engagement scores, recent signals, and the current AI summary. No middleware. No complex integration. Structured JSON designed for AI agent consumption.
How it works
Product Tracking Skills bring clean data in
Open-source AI skills audit your tracking, design a measurement plan, and generate instrumentation code. Clean, comprehensive product data flows in from Segment, PostHog, Amplitude, and 25+ other sources. A tracking watchdog monitors coverage as new features ship, so the data feeding your scores never goes stale.
Accurate scoring means accurate context
Engagement scores reflect real product value because you configure which behaviours matter and how much each contributes. The result is scores, segments, and summaries that accurately represent account health — so your AI agents always work from accurate context. Coming soon: AI will review your weighting and suggest improvements automatically.
Structured context flows to every AI tool
The finished intelligence reaches every AI tool in your stack. Intercom Fin, Zendesk AI, Atlassian Rovo, custom GPTs, LangChain agents, internal copilots — they all get structured JSON via REST API and webhooks. One call returns scores, trends, segments, risk signals, and AI summaries. Always current. Always structured. Always privacy-aware.
Clean data in, optimised scoring, intelligence out to every tool. No other engagement platform has this stack.
Integrations & actions
AI Context reaches every agent and tool in your stack. API access is included on all plans — not locked behind enterprise pricing.
REST API
Full engagement profiles for any account or user — scores, deltas, segments, risk signals, activation status, and AI summaries. Structured JSON, single call, documented and versioned. Build AI agent integrations in hours, not weeks.
API documentationWebhooks
Push engagement changes to your systems in real time. Score threshold crossings, segment transitions, and risk signal activations trigger outbound events your AI workflows can act on immediately.
CRM and support tool sync
Engagement data syncs to HubSpot, Salesforce, Attio, Intercom, and Zendesk. AI tools that read CRM or support context — including Rovo and Fin — pick up live engagement data without separate integration.
See integrationsCRM Sync
Engagement data in HubSpot, Salesforce, Attio — visible to AI tools that read CRM.
What this unlocks
For customer success
- AI support agents triage tickets using live engagement scores — a score-23 account gets immediate escalation, a score-95 power user gets confident self-serve guidance
- Intercom Fin and Zendesk AI access the AI summary before drafting a response, adjusting tone and urgency based on real account health
- Proactive outreach triggers when score drops pair with declining user counts — before the customer raises a ticket
For product teams
- Custom GPTs and LangChain agents query engagement data to answer "which accounts adopted the new feature?" or "what's the activation rate for the latest cohort?"
- Internal copilots generate portfolio health summaries on demand — no analyst queue, no dashboard building
- AI-powered alerting when engagement patterns shift after a release, surfacing impact faster than manual review
For sales & revenue
- Atlassian Rovo and sales copilots pull engagement data into pre-call briefs — reps walk in knowing exactly how deeply the account uses the product
- Expansion timing driven by engagement trajectory — usage patterns and segment membership signal when accounts are ready to grow
- Renewal prep includes AI-generated account summaries showing engagement trend, champion activity, and feature adoption depth
For leadership
- Ask Claude or an internal copilot "how's our customer health this week?" and get a real answer grounded in live engagement data, not a slide deck from last month
- AI-generated briefings for board prep that pull directly from account scores, segment distributions, and trend data
- Confidence that every AI tool across the company — support, sales, ops — is working from the same engagement truth
Give your AI agents real customer intelligence
One API call. Structured JSON. Engagement scores, risk signals, usage trends, and AI-ready summaries — delivered to every AI tool in your stack.
- API access on all plans — not enterprise-only
- Structured JSON designed for AI agent consumption
- Privacy-aware — engagement intelligence, never PII
- Works with Intercom Fin, Zendesk AI, Atlassian Rovo, custom GPTs, LangChain, and any agent framework