It reads, continuously
Sources are connected once and read all the time, so the pass is finished overnight rather than run as a quarterly project.
[ 01 | THE DEFINITION ]
Agentic customer intelligence, in two sentences
DEFINITIONAgentic customer intelligence is customer intelligence produced by software agents that read customer and market signals continuously, connect each signal to the accounts and revenue it touches, and recommend or take the next action with the evidence attached. It replaces dashboards a person has to check and reports a person has to interpret with a read that is already done, priced and owned when the team arrives.
It connects, across sources
A competitor move, the tickets that followed it and the accounts that raised them sit on one signal layer, so cause and effect can be measured rather than guessed.
It acts, with evidence
Each finding arrives as a play with an owner, a confidence score and the records behind it, at the autonomy the team sets: Advisory, Supervised or Autopilot.
[ 02 | WHAT IT IS NOT ]
How it differs from the tools that came before it
These categories are useful and many teams keep one alongside HyperOrbit. The difference is what happens after the data is collected.
Versus VoC and feedback-analytics platforms
Those platforms categorise feedback and report volume and frequency, usually within the feedback you already exported. Agentic customer intelligence reads every channel continuously, prices each theme by the ARR behind it, and hands over the action rather than the chart.
Versus research repositories
A repository stores interviews and recordings and lets researchers tag and search them. The analysis stays researcher-led and deliberate. Agents do the reading and the tagging themselves, and keep the read current as new signals land.
Versus feedback boards
Boards hear the customers who take the time to post and vote. Agents read the customers who never post: the calls, tickets and reviews where most of the signal lives, and the competitor move that caused a spike.
Versus dashboards and BI
A dashboard shows a number and waits to be checked. An agent notices the number moved, finds the cause, prices the exposure and brings it to the owner with a recommended play.
Versus asking ChatGPT
A general assistant knows nothing about your accounts and cannot read your ticket queue. Agentic customer intelligence is grounded in your own connected sources, cites the records behind each answer, and refuses to invent what the data does not hold.
Versus a team of analysts
Analysts are the model. The agents do the labour they would do if they had time to read everything, every day, and the team keeps the judgement: humans approve, agents do the work.
[ 03 | HOW HYPERORBIT DOES IT ]
Three agents, one signal layer
HyperOrbit is an agentic customer intelligence platform for product, CX and revenue teams. Three agents, Chorus, Recon and Atlas, read every call, ticket, review, competitor move and usage signal, connect each one to the accounts it touches, and hand the team the action with the evidence and the revenue behind it.
Chorus, the voice-of-customer agent
Clusters reviews, calls, tickets and surveys into ranked themes and sub-themes, each with the quotes behind it and the ARR of the accounts that raised it.
Recon, the competitive intelligence agent
Watches competitor sites, changelogs, pricing pages and reviews every day, scores each move, and drafts a battlecard for the ones that matter, held for review.
Atlas, the account intelligence agent (beta)
Fuses what Chorus and Recon find with usage, support and CRM data into one health score per account, then watches every churn and renewal window you set.
THE SIGNAL DESKAsk once and every agent answers: one question routed across Chorus, Recon and Atlas, with the sources cited. See the Signal Desk ›
[ 04 | GLOSSARY ]
The 25 terms this site uses, defined once
Linkable: every term has its own anchor. Numbers quoted here come from the worked example described on the methodology page.
- Agentic customer intelligence
- Customer intelligence produced by software agents that read customer and market signals continuously, connect them to accounts and revenue, and recommend or take the next action with the evidence attached, instead of dashboards a person has to check and interpret.
- Agent
- A piece of software with a job, a set of sources it reads, a confidence rule, and a level of autonomy. HyperOrbit runs three: Chorus, Recon and Atlas.
- Signal
- One customer or market event worth reading: a review, a ticket, a call transcript, a survey response, a competitor pricing change, a usage drop. Signals are the raw material; insights are what the agents make from them.
- Source (connector)
- A system the agents read from over OAuth, connected once and read continuously. HyperOrbit lists 76 connectors across calls, chat, CRM, support, reviews, surveys and product analytics.
- Signal layer
- The shared store every agent reads from and writes to, so a competitor move and the customer reaction to it sit on one clock and can be tied together.
- Theme
- A cluster of signals that mean the same thing, grouped by intent rather than by keyword. In the worked example on this site, 100 pieces of feedback become 8 themes.
- Sub-theme
- A narrower cluster inside a theme. The same worked example carries 35 sub-themes under its 8 themes, each with a mention count and the quotes behind it.
- Insight
- A ranked finding, not a row: a theme, competitor move or account risk with its evidence, its confidence and the ARR behind it. Starter plans count insights per month.
- Evidence
- The records an insight rests on, one click away: the quotes, tickets, transcripts, page diffs or usage events that produced it.
- Confidence score
- How sure an agent is, stated as a percentage with the evidence behind it. An agent that cannot say how sure it is cannot be trusted with anything that matters; if it is 68% sure, it says 68%.
- ARR touched
- The annual recurring revenue of the accounts behind a theme, reaction or risk, priced from your CRM. It turns “customers are unhappy” into a number a CFO can act on.
- Competitor move
- A detected change at a competitor: a launch, a pricing change, a changelog entry, a review pattern. Recon detects and scores moves daily.
- Cause and effect (lag)
- The measured gap between a competitor move and the customer reaction that followed it. In the worked example, a free-tier launch was followed 8 days later by 31 more SMB pricing complaints.
- Battlecard
- A counter-brief for one competitor move, drafted with the evidence and a confidence score, held for your review unless you set Autopilot.
- Win/loss analysis
- Working out why deals are won and lost from the signals that already exist (CRM notes, calls, tickets, reviews, competitor mentions), rather than only from after-the-fact interviews.
- Account health
- One score per account that fuses feedback, usage, support and CRM signals, with the factors explained.
- Churn risk
- The likelihood an account will not renew, read from the same fused signals and stated with its confidence and the accounts renewing inside your window.
- Renewal window
- The period before a contract renews during which every agent stops and asks before acting on anything that touches the account.
- Play
- A recommended action for an account, theme or move, drafted with the evidence, an owner and a confidence number, approved in one click or run on Autopilot.
- Autonomy modes
- Advisory suggests, Supervised waits for your click, Autopilot acts within limits you set and logs every decision. Set per agent.
- Guardrails
- The rules an agent cannot cross whatever its autonomy: on this platform, anything touching pricing or an account inside its renewal window stops and asks.
- Signal Desk
- HyperOrbit’s single question box: one query routed across Chorus, Recon and Atlas, answered with cited sources.
- Voice of customer (VoC)
- The discipline of reading what customers say across channels and turning it into decisions. Chorus is HyperOrbit’s voice-of-customer agent.
- Competitive intelligence (CI)
- Tracking what competitors do and deciding how to respond. Recon is HyperOrbit’s competitive intelligence agent.
- Account intelligence
- A continuous read on each account’s health and risk, fused from every other signal. Atlas, in beta, is HyperOrbit’s account intelligence agent.
[ 05 | GO DEEPER ]
Related on hyperorbit.ai
HOW IT WORKSCapture, connect, actThe pass, the signal layer and the autonomy modes, step by step.
METHODOLOGYWhat every number measuresThe worked example, the medians and the comparison rules behind the figures on this site.
COMPAREDBest voice of customer softwareEight tools on six criteria, HyperOrbit included, written to be defensible.
PRICINGStart free, scale by sourcesStarter is free: one feedback source and one competitor source. Enterprise removes the limits.
[ 06 | FAQ ]
Questions people ask about the term
What is agentic customer intelligence?
Customer intelligence produced by software agents that read customer and market signals continuously, connect each one to the accounts and revenue it touches, and recommend or take the next action with the evidence attached. The team keeps the judgement; the agents do the reading.
How is it different from a voice-of-customer platform?
A VoC platform categorises the feedback you give it and reports volume and frequency. Agentic customer intelligence reads every connected channel all the time, prices each theme by the ARR of the accounts behind it, links reactions to the competitor moves that caused them, and hands over a play rather than a chart.
Is it just AI applied to customer feedback?
No. The models do the reading, but the defining parts are continuous connection to your sources, one shared signal layer across customer and market data, a confidence score and evidence on every finding, and an action with an owner at the end.
How is it different from asking ChatGPT about my customers?
A general assistant cannot read your tickets, calls or CRM, and it will answer confidently without evidence. Agentic customer intelligence is grounded only in your connected sources, cites the records behind each answer and declines when the data does not support one.
Do you need all three agents?
No. Starter runs Chorus on one feedback source and Recon on one competitor source for free. Atlas, in beta, compounds on the other two and is part of Enterprise.
Who uses agentic customer intelligence?
Product teams deciding what to build or stop building, customer success and revenue teams protecting renewals, and product marketing tracking competitor moves and message fit.
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