Own the answer at portfolio scale.
Enterprise brands don't need another dashboard. They need the narrative strategy behind AI recommendations, run with them: analyst-grade interpretation, portfolio-scale frame mapping, dedicated guidance. Built on public AI answers, with no access to your customer data required.
✓ 30 minutes with a narrative strategist · we run your category live on the call and show you whose frame the answers are built on
Scale you inherit on day one.
ChatGPT, AI Overviews, AI Mode, Gemini, Claude, Perplexity, Copilot, Grok — every day, not on demand. Your baseline starts pre-warmed.
Longitudinal answer history from day one — the trend line a tool you install next quarter can’t backfill.
Your workspace lives where you choose. Crawling routes by target market independently.
Every number on this page is queryable by your own agents and BI, not trapped in our dashboard.
AI search doesn't rank your brand.
It recommends a story.
The brand whose frame the model has adopted gets the recommendation. Most tools hand you a score and a mention count: a downstream symptom. At enterprise scale the question isn't are we mentioned; it's whose frame is the answer built on, and why.
A dashboard tells you you're losing. Mavel tells you why: the frame the model learned, the sources it weighted, and where to intervene. Insight arrives as prioritised decisions, not raw data.
A portfolio has many narratives, and they interact. Mavel maps the prompt universe of your categories into one consistent strategic view of representation, not a dashboard per product per market.
A dedicated strategic partner scopes, diagnoses and prioritises with your team. The output is narrative strategy, not a monthly report: what to publish, correct and build consensus around.
Not a tool. A three-layer platform.
Every Mavel product runs on the same core: an AI infrastructure layer that orchestrates agents, knowledge and execution. Universal capabilities compose into products, so what you buy today is the first surface of a much deeper system.
The surfaces your teams work in: live today, with the next wave built on the same core.
Universal abilities any product can compose. The same understanding of your site, brand and market powers every surface.
The engine. Not sold directly: it runs everything above.
The ecosystem play: because the core is universal, it won't stop at our own products. SDK & API access for partners is on the platform roadmap; enterprise customers get it first through Enterprise API & integrations.
Describe the outcome.
The platform builds the workflow.
Not a block editor. You state the job in plain language and the platform turns it into an orchestrated process of agents running on the Mavel core.
▸ "Every Monday, analyse five competitors, find new features, assess the impact on our roadmap, prepare a report and update the comparison page."
One sentence in, a scheduled, multi-agent workflow out. Scoped, monitored and rerun weekly on the platform.
Your agents are first-class citizens.
Every competitor will show your team a dashboard. Mavel is the only narrative-intelligence layer built agent-first: the same data your analysts see is live for Claude, Cursor, your BI and your internal agents — over MCP and a versioned REST API, governed by enterprise OAuth.
✓ connected · 41 tools · workspace-scoped OAuth
> which competitor gained narrative share this quarter?
● mavel.narrative_share({ period: "90d" })
top mover: competitor-b +6.2pt · driver: comparison articles
Enterprise-grade by default.
Portfolio-scale by design
Enterprise-grade controls
Your data, your rules
Done with you, not handed off
High-touch, done-with-you.
A dedicated strategic partner scopes the categories, buying stages and prompt sets that matter to your business.
We identify the sources and frames shaping AI recommendations in your space: where your representation is absent, wrong, or ceding ground.
The diagnosis becomes an ordered action set: what to publish, what to correct, what to build consensus around.
Ongoing monitoring, managed ops if you want them, and a live narrative review with your CSM. Strategy, not a monthly report.
Your strategic partner maps categories, competitors and buying stages with your team, and the first full 8-engine scan runs. One working session; about two hours of your team's time.
Frame and source analysis lands as an ordered action list: what to publish, what to correct, what to build consensus around. Reviewed together, not thrown over the wall.
Daily tracking is live across the portfolio, the action loop is running, and the review rhythm below takes over. Expect two to four hours per week from your team during onboarding, less after.
A live working session to stand up your portfolio, not a help-center link.
Weekly during the first month. Your strategist walks the moves, not the metrics.
Questions go to the people who run your analysis, with a response-time SLA.
Where the category is moving, what the models changed, what to do next quarter.
Results, not promises.
How Chanty competes for AI answers in a category framed by giants — mapping the prompt universe of team chat, correcting the model's frame, and measuring the shift engine by engine.
READ THE CASE STUDY →Built on public answers.
Mavel works from publicly observable AI answers and public sources: the same outputs any user of ChatGPT, Gemini, Perplexity or Google AI Overviews can see. Our analysis does not require access to your customer data, PII, proprietary systems or internal infrastructure.
Where enterprise requirements go further, Enterprise agreements do too: SSO/SAML, advanced permissions, DLP and governance controls, US/EU/APAC data residency, custom retention policies, an on-premise option, and MSA & HIPAA-compliant engagement paths.
- SOC 2: not yet certified, stated plainly — it's on our roadmap, and we publish a date only when an auditor is engaged. Full status on the security page.
- Workspace context is never used to train models — ours or our providers'.
- EU workspaces live in EU infrastructure end to end; US likewise. You choose at signup.
- Available on request for your security review: DPA, subprocessor list, data-flow diagram.
- Workspace data is deleted on contract end under your retention policy.
- Security reviews and custom contracts are handled directly with your procurement and legal teams.
How is Mavel different from tools that track AI mentions?
Mention-tracking tools measure whether your brand appears in an AI answer, which is a downstream output. Mavel reads the upstream narrative: the frame the model adopted, the sources driving it, and why a competitor is being recommended. You fix the cause rather than monitor the symptom.
What happens on the first call?
Thirty minutes with a narrative strategist, not a discovery-questions gauntlet. We run your category live, show you whose frame the current answers are built on, and leave you with two or three concrete observations whether or not you buy anything.
What data does Mavel need from us?
None from your internal systems. Our analysis runs on publicly observable AI answers and public market sources. We need context from your team (categories, competitors, strategic priorities), but not access to customer data or proprietary infrastructure.
Can Mavel work across multiple brands or client accounts?
Yes. Multi-brand portfolios and agencies with enterprise clients are a core use case. Engagements are scoped to cover the categories and prompt sets relevant to each brand, with a consistent analytical frame across the portfolio.
Can our agents and BI use Mavel data directly?
Yes — that's the default, not an add-on. The MCP server exposes 41 tools under OAuth grants you control per agent; the versioned REST API publishes an OpenAPI spec; Looker Studio connects for reporting. If your stack can call an API, it can query your narrative data.
Can Mavel run in our environment?
Yes. Enterprise deployments support US, EU and APAC data residency, custom data retention policies, and an on-premise option for the analysis layer. Access is governed by SSO/SAML with advanced roles and DLP controls.
The answer is being written. With or without you.
Somebody's frame is already the one the models recommend in your category. Find out whose — on the first call, not after a quarter of onboarding.
- See whose frame the answers use today
- Leave with a prioritised first action set
- In production by week four
The narrative layer of AI search. Win the story the model tells, not just the mention.
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