Create Market-Backed Content

Create content from the voice of your market.

Content Engine mines customer conversations, objections, proof points, competitors, topics, and pipeline context to recommend, brief, write, score, and publish content grounded in real buyer evidence.

Content EngineTurn customer voice into content strategy, briefs, and publish-ready assets.
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Customer voice becomes content

Your market is already telling you what to write.

Most content teams are separated from the richest source of market intelligence: sales and customer conversations. GTM Engine connects transcripts, activities, contacts, accounts, opportunities, topics, objections, desired outcomes, proof points, and customer language, then turns that evidence into content strategy and production.

Evidence lineage

Market demand updated

VP Sales

“Our reps lose hours reconciling five systems before forecast.”

Sales call · Adobe

RevOps Director

“The real issue is trust. Nobody believes the CRM fields.”

Customer interview · Figma

CRO

“I need to know why a deal changed, not just that it changed.”

Discovery call · Notion

Structures
→

Content hotspots

1
2
3
GAP
5
6
7
8
9

Recommended topic

Why CRM data loses trust

28 sources · High pipeline relevance

Creates
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Content Studio

Draft

The Hidden Cost of Untrusted CRM Data

12 customer quotes8 proof points4 citations

94

Brand

87

SEO

100

Evidence

Every claim can retain a path back to the conversation, customer, opportunity, and market signal that produced it.

The operating flow

How Content Engine turns signal into action.

Follow the full process from the first decision through the resulting revenue action. Each stage builds on the records, evidence, and outcomes created before it.

Mine evidence from sales and customer conversations

Every claim can trace back to the customer conversation that produced it.

Content Engine starts with connected evidence, not a blank prompt. It turns customer and prospect conversations into reusable content intelligence with source metadata.

  • Content Engine consumes transcript topics populated by transcript workflows.
  • Evidence extraction stores pains, objections, desired outcomes, customer language, proof points, quotes, competitors, and social ideas.
  • Evidence extraction runs for eligible transcripts with external participants linked to GTM contacts.
  • Evidence links retain transcript, activity, contact, account, opportunity, topic, excerpt, speaker, confidence, and source metadata.
  • Snippets can identify the specific participant or contact behind a quote when the model can confidently identify them.

Find content opportunities with Content Intelligence

Sell content strategy before writing.

Content Intelligence helps teams see demand, coverage, gaps, objections, questions, and recommendations from live GTM evidence.

  • Content Intelligence includes Hotspots and Recommendations tabs.
  • Hotspots has a Topic x ICP-or-Industry grid with Demand, Coverage, and Blended toggles.
  • Selecting a topic, persona, or industry shows scoped records, coverage, AI content ideas, objections, and questions.
  • Market-signal cards include Win/Loss, Rising Topics, Topic Correlation, and Topic Trend Over Time.
  • Recommendations include Primary marketing, Social, Assets, and Internal resources.
  • Recommendation cards show asset type, proposed title, customer-voice hook, rationale, source topics, and one-click Send to Studio.
  • Topics with no asset coverage surface content gaps.

Generate evidence-backed briefs before drafting

Genie writes from a brief that separates verified evidence from gaps.

The brief is the trust mechanism: it gathers the record context, evidence, provenance, customer language, SEO context, and open questions before drafting.

  • Generate brief mines customer record, evidence, transcripts, org/product context into verified facts, provenance, voice-of-customer phrases, evidence-tagged outline, FAQ, information-gain notes, and open items.
  • Briefs are content-type aware.
  • Substantial assets are encouraged to brief first; lighter assets can draft directly.
  • Briefs can auto-research external SEO context including search intent, SERP competitors, People Also Ask, related searches, and recommended keywords.
  • SEO context is saved on the asset and surfaced with a SEO researched lapel.

Draft, edit, score, and review in Content Studio

Production workflow depth, not a generic writing canvas.

Content Studio gives teams one place to draft, revise, cite, comment, review, score, and version assets with Genie in context.

  • Content Studio is a single-canvas editor with title, metadata bar, content score, word count, reading time, metadata panel, SEO fields, Sources/Citations footer, and Genie drawer.
  • TipTap editor supports markdown output, headings, lists, blockquotes, links, tables, images, and videos.
  • Genie edits sections, headings, titles, draft markdown, and metadata fields.
  • Streaming edits highlight affected content in real time.
  • Inline comments and @mentions create review threads and notifications.
  • Send for review changes status and notifies reviewers.
  • Inline rewrite handles selected text with short prompts.
  • Versions save historical drafts and allow restore.

Apply brand, editorial, and SEO/AEO controls

Content controls are enforced across briefs, drafting, scoring, and review.

Content Engine differentiates from generic AI writing by making style, language, SEO/AEO, and editorial quality part of the workflow.

  • Content Engine Settings compose one canonical style guide from brand voice, structure, language, AEO rules, anti-patterns, humor/metaphors, target audience, personas, segments, distribution channels, do say/do not say, boilerplate, reading level, SEO limits, and article structure template.
  • Style guide is injected into Studio Genie, content brief, and editorial review.
  • Do-not-say terms are enforced by editorial review and avoided by Genie.
  • Editorial review checks AI-slop patterns, banned terms, style-guide violations, readability drift, and em dash rules.
  • Scorecards include overall, quality, uniqueness, helpfulness, SEO/AEO readiness, Flesch-Kincaid grade, and editorial verdict.
  • SEO metadata includes slug, meta title, meta description, canonical URL, focus keyword, secondary keywords, OG image/alt, Twitter card, schema type, noindex, and reading time.

Manage the content operation

Content Engine is an operating system, not only a writing surface.

Teams can manage inventory, schedule work, refresh scores, coordinate review, and publish to CMS from the same content system.

  • Content Library includes KPI strip for content gaps, inventory, SEO/AEO readiness, average score, and scheduled content.
  • Library supports filters, inventory table, content-type changes, status changes, score columns, author filter, stale score refresh, create new content, and delete.
  • Content Calendar includes month/week/day views, status/type filters, backlog, Suggestions, Library, New idea tabs, drag-and-drop scheduling, Suggest week, drawer editing, and Create draft.
  • CMS publishing currently supports Sanity with schema-driven publish dialog, required-field handling, reference fields, SEO field mapping, Draft/Live toggle, external refs, and Open in Sanity link.

Platform architecture

One outcome, powered by one connected platform.

These are not separate point products. Each module reads from and contributes to the same identity, activity, intelligence, and action layer.

Shared foundation

Unified revenue data model

Module 01

Unified Revenue Data

Transcripts, activities, contacts, accounts, opportunities, topics, excerpts, speakers, confidence, and source metadata stay connected.

Module 02

Content Engine

Content Intelligence, briefs, Studio drafts, evidence chips, editorial review, scorecards, comments, versions, library, calendar, and CMS publishing operate together.

Module 03

SEO/AEO & Brand Controls

Style guide, do-not-say terms, editorial verdicts, SEO metadata, schema settings, scorecards, and research context keep output governed.

Choose your starting point

Start where the pain is sharpest.

Enter through one measurable workflow, then expand without rebuilding the data foundation.

Path 01

Start with customer voice

Mine calls and transcripts for the topics, objections, outcomes, and phrases buyers actually use.

Shared model → This workflow → Expand
Path 02

Start with content gaps

Find high-demand, low-coverage topics by ICP, industry, objections, questions, and source evidence.

Shared model → This workflow → Expand
Path 03

Start with production control

Move from recommendation to brief, draft, score, review, schedule, and publish without losing citations.

Shared model → This workflow → Expand

Why GTM Engine

Built for evidence-backed content intelligence, not generic generation.

Content Engine combines customer evidence, GTM records, style constraints, SEO context, review workflow, and CMS publishing so content is grounded in what buyers actually say.

Comparison 01

Against AI writing tools

✓

AI writing tools generate text from prompts. Content Engine writes from connected customer evidence, GTM records, style constraints, citations, SEO context, and content operations.

Comparison 02

Against SEO tools

✓

SEO tools identify keywords. Content Engine combines search context with real buyer objections, desired outcomes, proof points, and customer language.

Comparison 03

Against call intelligence tools

✓

Call intelligence captures conversations. Content Engine turns those conversations into content strategy, briefs, drafts, enablement, scorecards, and CMS-ready assets.

Comparison 04

Against content calendars

✓

Calendars manage dates. Content Engine decides what should exist based on evidence, then helps create, score, review, schedule, and publish it.

Questions worth asking

Designed for evidence, control, and editorial trust.

Content Engine does not treat every transcript line as publishable fact. It uses filtering, confidence, citations, style controls, scorecards, and review to keep teams in control.

Adoption principle

Start with one painful workflow. Prove the outcome. Expand on the same model.

01AI content is generic.+

Content Engine starts from customer quotes, objections, proof, topics, source metadata, style guide, editorial review, and scorecards instead of a generic prompt.

02Marketing already has SEO tools.+

GTM Engine is not replacing SEO research. It adds proprietary market evidence from sales and customer conversations and connects it to briefs, content, and CMS workflows.

03Sales calls are messy and not always usable.+

Content Engine emphasizes external-participant filtering, confidence, source metadata, citations, and editorial review. It does not treat every transcript line as publishable fact.

04Content teams need control.+

Teams keep control through comments, review requests, versions, inline editing, status workflow, style settings, metadata, and draft/live publishing.

05How do we keep customer evidence private?+

Evidence can remain an internal research and citation layer. Teams decide which excerpts, claims, and proof points reach a draft, and editorial review remains part of the publishing workflow.

06Will this create more content instead of better content?+

Content Intelligence prioritizes demand, coverage gaps, pipeline relevance, and available evidence before drafting begins. The goal is to focus production on the opportunities the market has already validated.

Connected revenue motions

Use the same buyer intelligence across one-to-one and one-to-many activation.

The same buyer intelligence that tells sales who to contact and what angle to use also tells marketing what the market needs to hear.

Unified GTM Data Model

See how conversation evidence connects to accounts, contacts, opportunities, and workflows.

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Generate Pipeline

Use the same buyer intelligence for one-to-one outbound.

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Close Pipeline

Turn deal objections and competitive mentions into sales enablement.

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Automate RevOps

See the workflows that extract, structure, and govern customer evidence.

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See the team perspective

Marketing Leaders

Use customer language, attribution, and account data to drive campaigns and content.

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Sales Leaders

Turn trusted deal data into coaching, forecasting, and pipeline action.

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