Ambient customer intelligence
Build a Customer memory from every interaction — and put it to work across marketing, product, operations, growth, and beyond.
70% of what your customers say never reaches the decisions shaping their experience.
Customer feedback exists. But in its raw form—contradictory, nuanced, context-dependent—no dashboard, chatbot, or agent will get it right.
Dashboards, repositories, and reports
Data goes in. Nothing happens. User has to log in, crunch & interpret the data, and hope the right person acts. Very few do.
AI assistants (Chatbots)
Dashboards of the AI era. A snapshot of raw data in a moment of time. No visibility into trends, patterns, or context. No memory. No agency.
AI agents (RAG)
Customer feedback is contradictory, nuanced and context dependent which leads agents to hallucinate or stay shallow. No resolution, no compounding.
Listen, remember, and act
Built the way memory works — every customer interaction encoded, consolidated into a persistent memory, and recalled in your context to drive actions that move the needle.
Encode customer signals
Source-native agents optimized for every modality, format and structure. Signals are atomized into distinct data points and normalized across sources — made comparable without losing the nuance and context of where they came from.
Memory consolidation
Contradictions are resolved, noise is compressed, and your customer memory is consolidated in real time. Always learning, always current.
Memory at scale
Persona, competitor, journey, product, segment — distinct memories, each continuously updated with every new customer interaction or feedback.
Recall customer memory in your business context
Customer memory without your business context is not actionable. Your goals, roadmap, and priorities are the lens that turns customer memory into actions that matter — delivered into the workflows and tools your teams already use.
No deployment. No adoption. No behavior change.
Customer feedback is captured from the tools you already use. Actions are delivered into (other) tools your teams already use.
Genuinely intuitive solutions that solve real problems—not introduce more.
Deel's GTM team turns sales/cs calls into product messaging frameworks and marketing actions that drive conversion and growth.
Action turns customer feedback into faster fixes across stores and channels—earning favorite retailer of the year awards across EU markets.
Pledg prioritizes and drives the product roadmap and backlog with intelligence from customer and support feedback — directly in Jira and Slack.
↑25%
By uncovering the why behind the scores — and acting on it.
28%↓
lower churn
Spot churn drivers early. Act before customers leave.
↑21%
marketing conversion
Campaigns built on real customer language convert.
99%↓
analysis work
What used to take a team weeks is now fully automated.
Your data. Your rules.
Designed to meet the security, privacy, and compliance requirements of the most demanding enterprises.
Designed to meet the security, privacy, and compliance requirements of the most demanding enterprises.
Dedicated guidance
Deploy AI at scale with professional expertise.
Deploy AI at scale with professional expertise.
Total control
Manage models, data residency, MCP controls, privacy, and agent rules globally.
Manage models, data residency, MCP controls, privacy, and agent rules globally.
Premium support
Forward-deployed resources guarantee your success.
Forward-deployed resources guarantee your success.
Zero data retention
No training on your data by NEXT AI or LLM providers.
No training on your data by NEXT AI or LLM providers.
PII protection by default
Remove Personal Identifiable Information (PII) from your data with advanced models.
Remove Personal Identifiable Information (PII) from your data with advanced models.
Identity management
SAML-based SSO integration for secure user access.
SAML-based SSO integration for secure user access.
SCIM user provisioning
Easily create, update, and remove users and groups.
Easily create, update, and remove users and groups.
Bring your own model
Have a preferred AI vendor? Bring them to NEXT AI—we're LLM agnostic.
Have a preferred AI vendor? Bring them to NEXT AI—we're
Centralized security controls
Configure model access, MCPs, and agent rules.
Configure model access, MCPs, and agent rules.
Global compliance standards
Compliant with the requirements of GDPR and CCPA.
Compliant with the requirements of GDPR and CCPA.
Third-party security certifications
SOC 2 Type 2 certified and penetration testing.
SOC 2 Type 2 certified and penetration testing.
Robust data protection
AES-256 encryption at rest and TLS 1.2+ in transit.
AES-256 encryption at rest and TLS 1.2+ in transit.
Applied AI lab building ambient intelligence
We're helping many of the world's most ambitious companies change the way customer intelligence flows through their organizations.
Move faster, with confidence.
Ambient customer intelligence: for every team, in every workflow, every day.
Questions & Answers
What is NEXT AI?
What is a “Customer OS”?
Who is NEXT AI for?
What data sources can NEXT AI ingest?
What questions can teams ask in NEXT AI?
How does NEXT AI reduce manual work?
What are “Modes in chat” and why do they matter?
How is NEXT AI different from ChatGPT?
Can NEXT connect insights back into our tools?
Can we use our own AI model?
How does NEXT AI learn our product and terminology?
How does NEXT AI handle PII and privacy?
Does NEXT AI train on our data?
What security and compliance standards do you support?
What does onboarding look like?
Questions & Answers
What is NEXT AI?
NEXT AI is an AI-powered customer intelligence platform that turns messy customer signals (calls, tickets, surveys, reviews, community posts, and more) into ranked drivers and next-best actions your teams can execute.
What is a “Customer OS”?
A Customer OS is the operating layer that unifies customer feedback, understands what customers are saying, and pushes the results back into the flow of work so teams can act faster and with confidence.
Who is NEXT AI for?
NEXT AI is built for product, marketing, CX/VoC, insights, and customer support/care teams that need reliable answers from customer interactions—without manual analysis or dashboards.
What data sources can NEXT AI ingest?
NEXT AI can ingest and analyze calls, tickets, surveys, reviews, and community posts. NEXT AI can also access data/metrics from your existing tools via MCP—then enrich answers with context from systems like Confluence, Amplitude, Mixpanel, or Databricks.
What questions can teams ask in NEXT AI?
Teams can ask “what’s driving churn?”, “what objections are trending?”, “what should we fix next?”, or “how do segments differ?” and get structured answers with themes, prioritization, and supporting evidence.
How does NEXT AI reduce manual work?
NEXT AI replaces manual tagging, synthesis, and reporting by automatically clustering themes, quantifying drivers, and producing decision-ready outputs (marketing campaigns and messaging, product roadmap and PRDs, comparisons, updates) on demand.
What are “Modes in chat” and why do they matter?
Modes are purpose-built experiences for recurring work like clustering themes, comparing segments, or validating hypotheses—so teams can get consistent, repeatable outputs at scale.
How is NEXT AI different from traditional VoC tools or dashboards?
Traditional VoC tools often focus on collection and reporting. NEXT AI focuses on understanding + execution: it detects and quantifies themes and pushes results into workflows so decisions and actions happen faster.
How is NEXT AI different from ChatGPT?
Organizations need more than an assistant that answers from pasted context. NEXT AI is purpose-built to connect to real customer sources continuously, offer maximum evidence and feedback coverage, combine qualitative and quantitative signals, enable comparisons across stores, regions, journeys, and time, push outputs into store playbooks and product backlogs, and meet enterprise expectations for governance and privacy across demanding European markets.
Can NEXT connect insights back into our tools?
Yes. NEXT can trigger alerts, share stakeholder updates, and sync answers into tools like Jira, Salesforce, and Slack—so actions happen where teams already work.
Can we use our own AI model?
Yes. NEXT is LLM-agnostic, so you can choose the provider/model that best fits your security, cost, and data residency needs—with centralized controls. You can even bring-your-own-model by connecting your pre-approved endpoint to NEXT AI. Learn more at Data processing location (data residency).
How does NEXT AI learn our product and terminology?
With the Context Engine, you feed NEXT AI your products, services, journeys, and strategy so answers are grounded in your business context—not generic summaries. Furthermore, your teams can create data agents that organize and interpret data the way they work.
How does NEXT AI handle PII and privacy?
NEXT AI offers advanced data redaction models that remove personally identifiable information at the point of entry and provides enterprise controls over integrations, policies, and agent rules to keep usage safe.
Does NEXT AI train on our data?
No. NEXT AI supports zero data retention and does not train models on your data (including LLM providers). Learn more at AI Supplementary Terms.
What security and compliance standards do you support?
NEXT AI supports SOC 2 Type II, SSO (SAML), SCIM provisioning, encryption at rest/in transit, and GDPR/CCPA-aligned controls.
What does onboarding look like?
Most teams start by connecting 2–4 sources (e.g., support + calls + reviews), defining key taxonomies (products/journeys/personas), and rolling out repeatable workflows via modes and automations. You can expect to be up and running within days.