The intelligence layer underneath every customer decision your team makes.
Most companies have customer data scattered across 14 tools and zero context. Post-Sales Brain unifies every signal — calls, tickets, contracts, product usage, billing, the open web — into a living context graph your AI agents can actually reason against.
Plug in Claude Code, Codex, Claude Cowork, or your own apps. Build whatever your team needs. The Brain stays up to date — and remembers every decision.
Your stack stays. The thinking gets done above it.
Every AI agent you've ever tried failed for the same reason.
It wasn't the model. GPT-4 is smart enough. Claude is smart enough. The model was never the bottleneck.
The bottleneck is context. Every agent you deploy starts with the same handicap: it doesn't know your customers. It doesn't know what happened last quarter. It doesn't know who the champion is, what the contract says, or why you set that account to Watch three weeks ago.
So it hallucinates. Or it gives generic answers. Or it asks the CSM for context the CSM was hoping the AI would already have. Every team hits this wall. Here are the four ways it usually plays out:
You give Claude access to Salesforce
It hallucinates from stale CRM notes the AE wrote 14 months ago. The contact it references left the company in March. The “insight” it produces is worse than guessing.
You build a Zapier pipeline
It pipes data from A to B but doesn’t understand any of it. You get a Slack message when an invoice is overdue. You don’t get the fact that the invoice is overdue because the champion left and nobody re-signed the SOW.
You hire an FDE
They build a beautiful integration between Snowflake and your CRM. It works for three months. Then the schema changes, the FDE is on another project, and the pipeline rots. Silently.
You buy an AI platform
You get a chatbot over a search index. It can find documents. It cannot reason about relationships between customers, contracts, usage patterns, and team decisions. It’s Ctrl+F with a nicer UI.
What goes wrong without a context graph
| Scenario | Without Brain | With Post-Sales Brain |
|---|---|---|
| Is Modal at risk? | CSM checks CRM notes from 3 weeks ago, sees nothing. Renewal is in 40 days. | Brain shows usage down 38%, champion left 12 days ago, open P1 on core integration. Pulse Score dropped from 74 to 41. |
| Who’s the champion at Vercel? | Whoever the AE put in Salesforce 14 months ago. No one has verified since. | Brain maps every contact by meeting attendance, email recency, and deal involvement. Current champion: Sarah K., VP Eng, last active 3 days ago. |
| What worked last time we saved a deal this size? | Ask the senior CSM who “remembers something similar.” They’re on PTO. | Brain returns 4 decision records from similar saves: exec re-engagement + usage workshop drove 83% win rate on renewals >$200K. |
| Why did we set Arclight to Watch? | No one remembers. The CRM field just says “Watch.” | Decision record: Set to Watch on Oct 3 by Jordan M. Reasoning: 2 exec sponsors left in 6 weeks, new CTO is a Competitor-X alum. Linked to 3 Gong calls and a Slack thread. |
Your data wants to be a graph. It's just trapped in tables.
Tables are great for storage. They're terrible for relationships. Your CRM stores a contact. Your billing system stores an invoice. Your support tool stores a ticket. None of them know that the contact who opened the ticket is the same person whose invoice is overdue — and that they just posted about leaving their company on LinkedIn.
This isn't a new idea. Glean, Zep, Neo4j, and Anthropic's own MCP protocol are all converging on the same insight: agentic AI without a knowledge graph is like a self-driving car with no GPS map. The car is powerful. But it doesn't know where anything is.
Post-Sales Brain is the GPS map for your customer intelligence. Every entity has typed relationships, timestamps, provenance, and version history. Every fact is queryable. Every change is recorded.
Every fact has a timestamp. Every relationship has a source. Every change is recorded.
Four jobs the Brain does, continuously, for every customer.
1. Ingests every system of record, in real time.
The Brain connects to your entire stack and reads every event as it happens. No batch jobs. No nightly syncs. No CSV uploads.
| Source Event | Ingestion | Entity Extraction | Graph Commit |
|---|---|---|---|
| Gong call ended | Transcript + metadata | Contacts, sentiment, action items, topics | Episode node + 6 edges |
| Stripe payment failed | Invoice event webhook | Invoice entity, amount, account, overdue flag | Invoice node + account edge |
| LinkedIn job post | Profile change detected | Contact exit, new role, new company | Contact update + signal node |
| Snowflake usage drop | Warehouse query via dbt | Usage delta, feature breakdown, trend | Usage node + account edge |
2. Builds a context graph specific to post-sales.
Generic knowledge graphs treat every entity the same. The Brain ships with an ontology purpose-built for customer success, renewals, expansion, and support. Five core entity types. Typed relationships. Temporal properties on everything.
Most teams use 90% of the built-in ontology and customize the last 10%.
3. Records every action and decision with full provenance.
Most institutional knowledge lives in someone's head. When that person leaves, the knowledge leaves with them. The Brain treats decisions as first-class entities — recorded, linked, searchable, and reusable.
- • Renewal date moved from Nov 5 to Nov 19
- • Exec sponsor call scheduled for Nov 8
- • Usage workshop scheduled for Nov 12
- • Slack alert set for usage change > 10%
Every consequential decision lives in the Brain. Searchable. Auditable. Reusable.
4. Stays continuously up to date with no maintenance.
Every entity in the Brain carries a version history. Every relationship has a timestamp. When two sources disagree, the Brain surfaces the conflict with provenance instead of silently overwriting. Staleness is a bug, not a feature.
| Source | Last Sync | Latency SLA | Health |
|---|---|---|---|
| Salesforce | 12s ago | < 60s | |
| Gong | 47s ago | < 60s | |
| Stripe | 1m ago | < 5m | |
| Snowflake | 3m ago | < 5m | |
| Zendesk | 22s ago | < 60s | |
| Slack | 8s ago | < 60s | |
| 42m ago | < 1h | ||
| Jira | 2m ago | < 5m |
Nothing in the Brain ever “goes stale” silently.
The Brain is queryable from Claude Code, Cowork, Codex, and anything else your team builds with.
The Brain exposes an MCP server, a REST API, and raw Cypher queries. Any tool that speaks HTTP or MCP can read from the Brain, write to it, and subscribe to changes. That means Claude Code can pull customer context mid-task. Codex can reason against your entire account graph. And your team can build whatever they need — without waiting for us to ship it.
Custom Slack bot for AE-CSM handoffs
Query the Brain from Slack to pull deal context, stakeholder maps, and open risks the moment a deal closes. The CSM gets a full briefing without a single meeting.
Executive renewal command center
A live dashboard that pulls renewal forecasts, risk clusters, and expansion signals from the Brain. Your CRO sees the number and the reasoning behind it.
AI-powered QBR generator
Feed the Brain a customer name and get a draft QBR deck: usage trends, ROI metrics, open risks, recommended next steps. Built from real data, not templates.
Custom expansion model
Use the Brain’s usage patterns, contract structure, and stakeholder engagement data to score expansion readiness. Trigger outreach when signals converge.
Customer-facing AI support agent
An agent that answers customer questions using their own account context: contract terms, open tickets, feature roadmap, usage benchmarks. Grounded, not generic.
Internal “Ask anything” tool
Let any team member query the Brain in natural language: “Which customers adopted the new API in the last 30 days?” “What’s our average time-to-value for enterprise deals?”
Every Superhawk feature is downstream of the Brain.
Pulse Score, Work Queue, Coworkers, Briefings, Outside Signals, Ask Superhawk — every feature in the platform is a consumer of the Brain. They don't each maintain their own data layer. They query one shared, continuously-updated context graph. And so can your team's own tools.
Pulse Score
Computes health across six dimensions using the Brain’s live entity graph. Every score is explainable because the source data is linked.
Work Queue
Prioritizes tasks by querying the Brain for risk, renewal proximity, expansion signals, and CSM capacity. The queue updates as the Brain updates.
Coworkers
AI teammates that run motions — onboarding, renewal prep, escalation — using the Brain as their memory and reasoning substrate.
Briefings
Daily and weekly summaries generated from the Brain’s latest state. Every bullet links back to the entity or decision it references.
Outside Signals
Web-sourced intelligence — funding rounds, leadership changes, competitor mentions — ingested into the Brain and linked to account entities.
Ask Superhawk
Natural-language queries resolved by traversing the Brain’s context graph. Answers cite the source entity, timestamp, and confidence.
The Brain isn't a feature. It's the foundation. Every tool your team builds on the Brain inherits the same live data, the same decision history, and the same audit trail.
Built for the data your auditors will actually ask about.
Three weeks from contract to “the Brain is running our QBRs.”
Connect your stack
OAuth into your CRM, billing, support, product analytics, and comms. The Brain begins ingesting and building the graph.
Tune ontology + downstream apps
Customize entity types, relationship labels, and signal weights. Connect Coworkers, Pulse Score, and your first internal tool.
Custom apps
Build your first custom app on the Brain: a Slack bot, a QBR generator, an expansion model. The MCP server and REST API are live.
Full leverage
The Brain compounds. Decision history deepens. New team members onboard faster. Your AI coworkers get smarter every week.
Every CS org will need a Brain. The question is whether you build one or rent one.
There are three paths to a customer intelligence layer. Each one costs something different:
Wait for your incumbent
Gainsight, Totango, or your CRM vendor will eventually build something. Timeline: 18–36 months. In the meantime, your team runs on spreadsheets and tribal knowledge. Every quarter you wait, the knowledge debt compounds.
Build it yourself
You need a graph database, an ingestion layer, an entity resolution pipeline, a temporal model, an MCP server, and a team to maintain it. Estimated: 15 engineers, 18 months, and the ongoing maintenance tax that never ends.
Use Superhawk
Connect your stack in week one. The Brain starts ingesting immediately. Your team builds on top of it from day one. The context graph compounds every day. And you never hire an engineer to maintain a pipeline again.
The Brain is the highest-leverage investment a post-sales org can make. Not because of what it does today — but because every tool you build on it, every decision you record in it, and every agent you connect to it makes it more valuable tomorrow. That's compound leverage. And it only works if you start.
60+
Systems connected
<60s
Signal-to-Brain latency
6M+
Entities per typical Brain
0
Tribal knowledge debt
Common questions
How is a context graph different from a vector database or RAG?+
Vector databases store chunks of text and retrieve by similarity. RAG pipes those chunks into a prompt. Neither understands relationships between entities. A context graph stores structured entities (accounts, contacts, contracts, signals) with typed, timestamped relationships. When the Brain answers “Who is the champion at Modal?” it traverses a graph — it doesn’t search for the most similar paragraph.
Does the Brain require a data migration?+
No. The Brain connects to your existing systems via OAuth and API. It reads from your tools in real time. Your data stays where it is. The Brain builds a context graph alongside your existing stack, not instead of it.
How is this different from Glean?+
Glean is an enterprise search engine. It indexes documents and returns results. The Brain is a structured knowledge graph purpose-built for post-sales: accounts, contacts, contracts, signals, episodes, decision records. Glean finds a document that mentions a customer. The Brain knows that customer’s health score, their champion’s last meeting, and what happened the last time a similar account churned.
What about custom internal systems?+
The Brain ships with 60+ native connectors. For proprietary or internal systems, you can push data via the REST API or build a lightweight connector using our SDK. Most custom integrations take a few hours, not weeks.
What query interfaces does the Brain support?+
Three: a REST API for programmatic access, Cypher queries for graph traversals, and an MCP server for Claude Code, Codex, and Claude Cowork. Most teams use the MCP server day-to-day and the REST API for custom apps.
How does the Brain handle conflicting data?+
Every fact has a source, a timestamp, and a confidence score. When two systems disagree — CRM says $400K, billing says $380K — the Brain surfaces both with provenance and lets your rules or your team resolve the conflict. Nothing is silently overwritten.
Can I query the Brain at a point in time?+
Yes. The Brain is fully versioned. You can query the state of any entity as of any date. “What was Modal’s health score on September 15?” “Who was listed as champion before the reorg?” Both are first-class queries.
How does the Brain interact with Gainsight, Catalyst, or ChurnZero?+
The Brain ingests data from these platforms the same way it ingests from Salesforce or Zendesk — as a source system. If you use Gainsight for playbooks, the Brain reads those execution records and links them to the account graph. The Brain doesn’t replace your CS platform; it makes it smarter.
Can we customize the ontology?+
The Brain ships with a default post-sales ontology: Account, Contact, Contract, Signal, Episode. Most teams use 90% as-is and customize the last 10% — adding entity types like “Partner” or “Product Module,” or extending relationship labels to match their internal language.
Can the Brain handle large data volumes?+
A typical Brain holds 6M+ entities across hundreds of accounts. The graph is designed for sub-second query latency at that scale. For enterprises with 10K+ accounts, we partition the graph and optimize traversal paths during onboarding.
What happens if Superhawk goes down? Is there lock-in?+
Your source systems are untouched — the Brain reads from them, never writes back. If you cancel, your CRM, billing, support, and product analytics are exactly where you left them. We also offer full graph exports in standard formats.
How is the Brain priced?+
The Brain is included in every Superhawk plan. Pricing scales with the number of managed accounts and connected systems. We don’t charge per query, per entity, or per API call. Book a walkthrough and we’ll scope it for your team.
Your team's next great internal tool is one Brain connection away.
Connect your stack, watch the Brain populate, and start querying within an hour.