# Semarize

> The Conversational Intelligence API for turning calls, emails, and chats into structured semantic signals.



## Product
- [Semarize](https://semarize.com/index.md): The Conversational Intelligence API that turns calls, emails, and chats into structured semantic signals.
- [Pricing](https://semarize.com/pricing.md): Simple, transparent pricing that scales with usage.
- [Product Overview](https://semarize.com/product/overview.md): How Semarize converts unstructured conversations into structured semantic signals for automation, reporting, and CRM enrichment.
- [Bricks](https://semarize.com/product/bricks.md): The atomic semantic checks that produce structured conversation signals.
- [How It Works](https://semarize.com/product/how-it-works.md): How Semarize turns transcripts into versioned Bricks, Kits, and structured outputs.
- [Kits](https://semarize.com/product/kits.md): Reusable evaluation frameworks made from Bricks.
- [Knowledge Grounding](https://semarize.com/product/knowledge-grounding.md): Ground conversation evaluations in your product docs, playbooks, policies, and source material.
- [Semarize API](https://semarize.com/product/api.md): Send conversation content and a Kit ID, then receive deterministic JSON signals.

## Use Cases
- [Use Cases](https://semarize.com/use-cases.md): Ways to use Semarize across revenue, support, QA, AI evaluation, and data teams.
- [AI Evaluation](https://semarize.com/use-cases/ai-evaluation.md): Evaluate agent and workflow outputs against structured conversation evidence.
- [Customer Success](https://semarize.com/use-cases/customer-success.md): Turn customer conversations into health, risk, and expansion signals.
- [Data Science](https://semarize.com/use-cases/data-science.md): Feed analytics and models with typed signals instead of raw transcripts.
- [QA and Compliance](https://semarize.com/use-cases/qa-compliance.md): Score conversations against quality and compliance rubrics at scale.
- [RevOps](https://semarize.com/use-cases/revops.md): Extract deal, pipeline, and CRM enrichment signals from conversations.
- [Sales Coaching](https://semarize.com/use-cases/sales-coaching.md): Measure coaching signals from sales conversations without manual call review.

## Solutions
- [Solutions](https://semarize.com/solutions.md): Semarize solutions by team and industry.
- [Contact Centers](https://semarize.com/solutions/contact-centers.md): Turn contact center interactions into queryable QA and operational signals.
- [Enterprise Sales](https://semarize.com/solutions/enterprise-sales.md): Structured signals for complex enterprise sales cycles.
- [Financial Services](https://semarize.com/solutions/financial-services.md): Conversation intelligence for regulated financial services workflows.
- [Human Resources](https://semarize.com/solutions/human-resources.md): Extract structured evidence from HR and people conversations.
- [Professional Services](https://semarize.com/solutions/professional-services.md): Use conversation signals across client delivery and account work.
- [Retail and Ecommerce](https://semarize.com/solutions/retail-ecommerce.md): Extract structured customer and sales signals from retail conversations.
- [SaaS Technology](https://semarize.com/solutions/saas-technology.md): Conversation intelligence infrastructure for SaaS teams.
- [Telecom and Utilities](https://semarize.com/solutions/telecom-utilities.md): Conversation intelligence for telecom and utility customer interactions.

## Developers
- [API Reference](https://semarize.com/developers/api.md): Complete endpoint reference for the Semarize API.
- [Developers](https://semarize.com/developers.md): Developer documentation, quickstarts, examples, security, and MCP guidance.
- [Automation Patterns](https://semarize.com/developers/automations.md): Reference patterns for triggering, routing, and storing Semarize outputs.
- [Developer Quickstart](https://semarize.com/developers/quickstart.md): Start integrating Semarize into an application or automation workflow.
- [MCP](https://semarize.com/developers/mcp.md): Use Semarize through Model Context Protocol tools.
- [Security](https://semarize.com/developers/security.md): Security posture, authentication, data handling, and operational controls for Semarize.

## Resources
- [Resources](https://semarize.com/resources.md): Guides, playbooks, blog posts, and integration resources for Semarize.
- [Automation](https://semarize.com/resources/automation.md): Connect transcript pipelines to your automation stack - trigger analysis on new calls and route structured output to CRMs, Slack, or databases.
- [CRM & Data](https://semarize.com/resources/crm-data.md): Push structured conversation signals into your systems of record - CRMs, warehouses, and databases instead of raw transcripts.
- [Get Your Data](https://semarize.com/resources/get-your-data.md): Step-by-step guides for getting your calls, emails, and chats out of the tools you already use - APIs, bulk exports, permissions, and supported formats.
- [Playbooks](https://semarize.com/resources/playbooks.md): Ready-to-deploy kit stacks for sales coaching, RevOps, customer success, QA & compliance, AI evaluation, and data science. Pick a use case and start using it instantly in Semarize.
- [Adoption & Value Realisation Monitoring Playbook](https://semarize.com/resources/playbooks/adoption-and-value-realisation-monitoring.md): Evaluates whether customers are achieving intended outcomes and expressing measurable value. Detects ROI articulation, adoption barriers, and outcome misalignment to prevent churn and drive success.
- [AI Hallucination & Factual Accuracy Playbook](https://semarize.com/resources/playbooks/ai-hallucination-and-factual-accuracy.md): Evaluates AI-generated conversations for factual correctness and unsupported claims. Cross-references outputs against approved knowledge sources to detect hallucinations and accuracy issues.
- [AI Instruction Adherence Playbook](https://semarize.com/resources/playbooks/ai-instruction-adherence.md): Assesses whether AI-generated responses follow system instructions, brand tone, and formatting requirements. Flags deviations to ensure consistent and controlled AI behaviour.
- [AI Safety & Policy Enforcement Playbook](https://semarize.com/resources/playbooks/ai-safety-and-policy-enforcement.md): Evaluates AI outputs for safety violations, restricted content, and policy non-compliance. Ensures AI systems adhere to governance and regulatory standards.
- [AI Sales Agent Performance Playbook](https://semarize.com/resources/playbooks/ai-sales-agent-performance.md): Evaluates qualification accuracy, objection handling, and next-step clarity in AI-driven sales conversations. Measures performance against established sales methodology standards.
- [AI Support Agent Resolution Quality Playbook](https://semarize.com/resources/playbooks/ai-support-agent-resolution-quality.md): Assesses completeness and effectiveness of AI-driven support interactions. Detects unresolved issues, improper escalation handling, and policy deviations to maintain service quality.
- [Amazon Redshift](https://semarize.com/resources/crm-data/redshift.md): Load structured conversation data into Amazon Redshift.
- [AssemblyAI](https://semarize.com/resources/get-your-data/assemblyai.md): Retrieve transcripts from AssemblyAI's speech-to-text API.
- [Azure Synapse](https://semarize.com/resources/crm-data/azure-synapse.md): Load conversation data into Azure Synapse Analytics.
- [BigQuery](https://semarize.com/resources/crm-data/bigquery.md): Query conversation signals in Google BigQuery.
- [CallMiner](https://semarize.com/resources/get-your-data/callminer.md): Export conversation analytics and transcripts from CallMiner via API.
- [Chatbot Qualification & Routing Playbook](https://semarize.com/resources/playbooks/chatbot-qualification-and-routing.md): Analyses inbound chat conversations to ensure correct intent detection, qualification accuracy, and routing decisions. Supports improved lead conversion and operational efficiency.
- [Chorus](https://semarize.com/resources/get-your-data/chorus.md): Get conversation data from Chorus.
- [Churn Risk Early Warning Playbook](https://semarize.com/resources/playbooks/churn-risk-early-warning.md): Detects dissatisfaction, escalation signals, and renewal uncertainty in customer conversations. Generates churn risk indicators to support proactive intervention and retention strategies.
- [Clari Copilot](https://semarize.com/resources/get-your-data/clari-copilot.md): Get call transcripts and analytics from Clari Copilot via API.
- [Clay](https://semarize.com/resources/automation/clay.md): Enrich prospect data with conversation signals in Clay.
- [Competitive Intelligence Monitoring Playbook](https://semarize.com/resources/playbooks/competitive-intelligence-monitoring.md): Tracks competitor mentions, displacement narratives, and competitive sentiment across calls. Surfaces recurring themes and threat signals to inform positioning strategy and win-loss analysis.
- [Competitive Positioning Mastery Playbook](https://semarize.com/resources/playbooks/competitive-positioning-mastery.md): Assesses how confidently and accurately reps position against competitors. Detects differentiation clarity, battlecard alignment, and narrative strength to improve win rates in competitive deals.
- [Complaint Escalation Monitoring Playbook](https://semarize.com/resources/playbooks/complaint-escalation-monitoring.md): Detects high-severity complaints, legal risk language, and escalation triggers in conversations. Supports proactive intervention and compliance oversight.
- [CRM Hygiene & Stage Compliance Playbook](https://semarize.com/resources/playbooks/crm-hygiene-and-stage-compliance.md): Validates that conversational signals align with CRM stage definitions and deal progression criteria. Detects stage drift, missing mutual action plans, and inconsistent qualification to enforce process integrity.
- [Databricks](https://semarize.com/resources/crm-data/databricks.md): Store conversation signals in Databricks Lakehouse.
- [Deal Health Index Modeling Playbook](https://semarize.com/resources/playbooks/deal-health-index-modeling.md): Aggregates structured conversational signals into a composite deal health index. Enables revenue teams to quantify deal quality and correlate conversational behaviour with outcomes.
- [Deal Qualification Drift Detection Playbook](https://semarize.com/resources/playbooks/deal-qualification-drift-detection.md): Identifies deterioration in qualification quality across deals or segments. Detects shallow pain exploration, missing buyer validation, and inconsistent framework adherence to prevent pipeline inflation.
- [Deepgram](https://semarize.com/resources/get-your-data/deepgram.md): Retrieve transcripts from Deepgram's speech-to-text API.
- [Dialpad](https://semarize.com/resources/get-your-data/dialpad.md): Get call transcripts and recordings from Dialpad.
- [Discovery Excellence Playbook](https://semarize.com/resources/playbooks/discovery-excellence.md): Evaluates the quality and completeness of sales discovery conversations against a defined methodology. Measures depth of pain exploration, clarity of next steps, questioning quality, and alignment to internal discovery standards to improve rep execution and coaching outcomes.
- [Executive Communication Playbook](https://semarize.com/resources/playbooks/executive-communication.md): Assesses clarity, structure, and business alignment in executive-facing conversations. Measures strategic framing, outcome orientation, and communication confidence to improve C-suite engagement.
- [Executive Relationship Health Playbook](https://semarize.com/resources/playbooks/executive-relationship-health.md): Monitors executive sponsor engagement and strategic alignment in customer conversations. Detects declining executive participation and political risk to protect long-term account health.
- [Expansion & Upsell Identification Playbook](https://semarize.com/resources/playbooks/expansion-and-upsell-identification.md): Detects signals of growth opportunity within customer conversations. Identifies expansion intent, budget discussion, and product gap themes to support proactive revenue expansion.
- [Fathom](https://semarize.com/resources/get-your-data/fathom.md): Get meeting transcripts, summaries, and action items from Fathom.
- [Fireflies.ai](https://semarize.com/resources/get-your-data/fireflies.md): Get meeting transcripts and recordings from Fireflies.ai via GraphQL API.
- [Forecast Risk Early Warning Playbook](https://semarize.com/resources/playbooks/forecast-risk-early-warning.md): Identifies early indicators of forecast risk within deal conversations. Detects weak commitment language, vague timelines, procurement uncertainty, and risk omissions to improve forecast accuracy.
- [Gong](https://semarize.com/resources/get-your-data/gong.md): Get conversation data from Gong via API or bulk download.
- [Google Cloud SQL](https://semarize.com/resources/crm-data/google-cloud-sql.md): Store conversation data in Google Cloud SQL.
- [Grain](https://semarize.com/resources/get-your-data/grain.md): Get meeting recordings and transcripts from Grain via REST API.
- [HubSpot](https://semarize.com/resources/get-your-data/hubspot.md): Get call recordings and conversation data from HubSpot.
- [HubSpot](https://semarize.com/resources/crm-data/hubspot.md): Enrich HubSpot contacts and deals with conversation data.
- [Jiminny](https://semarize.com/resources/get-your-data/jiminny.md): Get call transcripts and coaching data from Jiminny via REST API.
- [Make](https://semarize.com/resources/automation/make.md): Create transcript processing workflows in Make.
- [Market Trend & Demand Signal Playbook](https://semarize.com/resources/playbooks/market-trend-and-demand-signal.md): Extracts emerging trends, recurring themes, and demand shifts from conversation data. Enables strategic insights for marketing, product, and executive decision-making.
- [MEDDICC Enforcement Playbook](https://semarize.com/resources/playbooks/meddicc-enforcement.md): Extracts and evaluates MEDDICC qualification signals from conversations. Scores completeness across metrics, economic buyer presence, decision process clarity, and champion strength to standardise qualification discipline across pipeline.
- [Microsoft Dynamics](https://semarize.com/resources/crm-data/microsoft-dynamics.md): Push structured conversation signals into Dynamics 365 records.
- [Microsoft Teams](https://semarize.com/resources/get-your-data/microsoft-teams.md): Get conversation data from Microsoft Teams meetings.
- [Modeling Best Practices](https://semarize.com/resources/crm-data/modeling-best-practices.md): Canonical guide to modeling Semarize outputs in any database or warehouse.
- [Multi-Threading & Stakeholder Coverage Playbook](https://semarize.com/resources/playbooks/multi-threading-and-stakeholder-coverage.md): Analyses stakeholder participation across pipeline to identify single-threaded deals and missing economic buyers. Supports pipeline de-risking and structured account coverage strategy.
- [Multi-Threading Conversation Playbook](https://semarize.com/resources/playbooks/multi-threading-conversation.md): Evaluates how effectively reps engage multiple stakeholders within a deal cycle. Detects role coverage, influence mapping, and stakeholder balance to strengthen deal resilience and reduce single-threaded risk.
- [n8n](https://semarize.com/resources/automation/n8n.md): Self-hosted automation pipelines with n8n.
- [Narrative Control & Storytelling Playbook](https://semarize.com/resources/playbooks/narrative-control-and-storytelling.md): Evaluates whether reps guide conversations with a structured narrative arc. Detects problem-solution framing, logical sequencing, and outcome reinforcement to improve persuasive communication.
- [Next-Step Discipline & Closing Momentum Playbook](https://semarize.com/resources/playbooks/next-step-discipline-and-closing-momentum.md): Ensures every call ends with clear, mutual next steps and defined ownership. Detects explicit commitments, timeline alignment, and action clarity to improve pipeline progression and forecast reliability.
- [Objection Handling Mastery Playbook](https://semarize.com/resources/playbooks/objection-handling-mastery.md): Assesses how effectively reps identify, categorise, and resolve objections in live conversations. Detects objection types, evaluates resolution quality, and measures value reinforcement to strengthen competitive positioning and conversion rates.
- [Observe.AI](https://semarize.com/resources/get-your-data/observe-ai.md): Get contact center interaction data from Observe.AI.
- [Otter.ai](https://semarize.com/resources/get-your-data/otter.md): Get meeting transcripts and summaries from Otter.ai.
- [Outreach](https://semarize.com/resources/get-your-data/outreach.md): Get Kaia conversation recordings and transcripts from Outreach via API.
- [Pipedrive](https://semarize.com/resources/crm-data/pipedrive.md): Enrich Pipedrive deals and contacts with conversation data.
- [Pipeline Narrative Consistency Playbook](https://semarize.com/resources/playbooks/pipeline-narrative-consistency.md): Compares conversational signals against CRM notes and forecast commentary to detect inconsistencies, omitted risks, or overconfidence. Supports forecast integrity and executive reporting accuracy.
- [PostgreSQL](https://semarize.com/resources/crm-data/postgresql.md): Store structured call data in PostgreSQL.
- [Pricing & Commercial Alignment Playbook](https://semarize.com/resources/playbooks/pricing-and-commercial-alignment.md): Evaluates pricing discussions for alignment with approved discount policies and commercial strategy. Detects unauthorised discount signals, weak value justification, and pricing inconsistencies.
- [Process Adherence & Stage Leakage Analysis Playbook](https://semarize.com/resources/playbooks/process-adherence-and-stage-leakage-analysis.md): Identifies patterns of process deviation and stage leakage across conversations. Extracts signals of skipped steps, weak commitments, and inconsistent qualification to inform operational improvements.
- [QA Coverage Playbook](https://semarize.com/resources/playbooks/qa-coverage.md): Applies a structured QA rubric to every conversation to replace sample-based quality assurance. Scores script adherence, empathy, policy compliance, and call handling standards at scale.
- [Question Strategy & Curiosity Playbook](https://semarize.com/resources/playbooks/question-strategy-and-curiosity.md): Analyses questioning behaviour to determine whether reps use open-ended, insight-driven questions that deepen understanding. Measures follow-up depth, listening behaviour, and interruption patterns to improve conversational quality.
- [Read.ai](https://semarize.com/resources/get-your-data/read-ai.md): Get meeting transcripts and analytics from Read.ai via webhooks.
- [Regulatory & Disclosure Verification Playbook](https://semarize.com/resources/playbooks/regulatory-and-disclosure-verification.md): Verifies that required legal disclosures and compliance statements are present and correctly phrased within regulated conversations. Flags omissions and potential policy breaches for audit readiness.
- [Rep Skill Development Tracking Playbook](https://semarize.com/resources/playbooks/rep-skill-development-tracking.md): Tracks behavioural and skill progression across conversations over time. Measures framework adoption, questioning improvement, objection handling development, and coaching delta to support structured enablement programs.
- [Salesforce](https://semarize.com/resources/get-your-data/salesforce.md): Access conversation data stored in Salesforce.
- [Salesforce](https://semarize.com/resources/crm-data/salesforce.md): Push structured call signals into Salesforce records.
- [Salesloft](https://semarize.com/resources/get-your-data/salesloft.md): Get conversation transcripts and recordings from Salesloft via API.
- [Sembly.ai](https://semarize.com/resources/get-your-data/sembly.md): Get meeting transcripts and notes from Sembly.ai via outbound automations.
- [Snowflake](https://semarize.com/resources/crm-data/snowflake.md): Load structured conversation data into Snowflake.
- [Stage Conversion Signal Analysis Playbook](https://semarize.com/resources/playbooks/stage-conversion-signal-analysis.md): Extracts conversational signals associated with successful stage progression. Identifies patterns in commitment language, stakeholder engagement, and objection resolution to improve conversion rates.
- [Supabase](https://semarize.com/resources/crm-data/supabase.md): Store structured conversation data in Supabase (PostgreSQL).
- [Symbl.ai](https://semarize.com/resources/get-your-data/symbl.md): Process and retrieve conversation intelligence from Symbl.ai's API.
- [tl;dv](https://semarize.com/resources/get-your-data/tldv.md): Get meeting transcripts and recordings from tl;dv via API.
- [Value Selling & ROI Articulation Playbook](https://semarize.com/resources/playbooks/value-selling-and-roi-articulation.md): Evaluates how effectively reps quantify business impact and articulate ROI during conversations. Detects outcome framing, financial justification, and personalised value alignment to strengthen executive-level selling.
- [Verint](https://semarize.com/resources/get-your-data/verint.md): Get conversation recordings and transcripts from Verint's enterprise APIs.
- [Voice of Customer Insight Extraction Playbook](https://semarize.com/resources/playbooks/voice-of-customer-insight-extraction.md): Extracts recurring pain points, objections, feature requests, and value language from customer conversations. Structures qualitative feedback into analysable themes for marketing, product, and strategy teams.
- [Win-Loss Signal Attribution Playbook](https://semarize.com/resources/playbooks/win-loss-signal-attribution.md): Identifies conversational patterns and signals that correlate with won or lost deals. Extracts objection categories, competitive presence, and qualification strength to support revenue modeling and strategic optimisation.
- [Workato](https://semarize.com/resources/automation/workato.md): Enterprise-grade call analysis automation with Workato.
- [Zapier](https://semarize.com/resources/automation/zapier.md): Build call analysis automations with Zapier.
- [Zoho](https://semarize.com/resources/crm-data/zoho.md): Push structured call signals into Zoho CRM records.
- [Zoom](https://semarize.com/resources/get-your-data/zoom.md): Get conversation data from Zoom meetings.
- [Zoom Revenue Accelerator](https://semarize.com/resources/get-your-data/zoom-revenue-accelerator.md): Get conversation intelligence data from Zoom Revenue Accelerator via REST API.

## Blog
- [100% QA Scoring Without Manual Review: Deterministic Rubrics for Every Call](https://semarize.com/resources/blog/100-percent-qa-scoring-without-manual-review-deterministic-rubrics.md): Manual QA sampling at 2–5% has two problems: coverage and consistency. Automated scoring with deterministic rubrics solves both - every call gets scored the same way, with no reviewer required to generate the result. The shift isn't just efficiency - it changes what coaching is built from and turns compliance verification from sampling into complete coverage.
- [AI Call Scoring Is Theatre Without a Knowledge Layer](https://semarize.com/resources/blog/ai-call-scoring-theatre-ground-it-in-pricing-and-icp.md): AI call scoring that runs on a good LLM with a well-written rubric can look accurate until you test it against what actually happened. The failure isn't one missing check. Every commercial dimension worth assessing has multiple facets, and each facet requires its own grounded document to evaluate properly. A knowledge layer is what makes scoring checkable across all of them rather than plausible about none of them.
- [AI scorecards are theatre unless they measure customer understanding](https://semarize.com/resources/blog/ai-scorecards-are-theatre-unless-they-measure-customer-understanding.md): Most AI call scorecards measure what the rep did - agenda set, questions asked, next step mentioned. That's measuring inputs. What actually matters is whether the buyer understood anything. The two are not the same thing, and the gap between them is where scorecard theatre lives.
- [AI Scorecards Don't Disagree. Your Prompt Does.](https://semarize.com/resources/blog/ai-scorecards-dont-disagree-your-prompt-does-evaluation-contract.md): Inconsistent AI scorecards aren't an AI problem - they're a process failure. Freeform prompts ask the model to re-interpret evaluation criteria on every run, and that interpretation drifts with phrasing, model updates, and context. The fix is an evaluation contract: a locked schema with defined output types that produces the same result on the same call, every time.
- [Blog](https://semarize.com/resources/blog.md): Perspectives on conversation intelligence, AI evaluation, and building systems that extract signal from unstructured data.
- [Bricks and Kits: the mechanism for stable conversation evaluation](https://semarize.com/resources/blog/bricks-and-kits-stable-conversation-evaluation.md): Freeform prompts produce inconsistent evaluation results - scores drift, output shapes change, and you can't tell whether coaching improved anything or whether the rubric moved. Bricks define a locked evaluation schema: one question, one output type. Kits group them into reusable evaluation workflows. The result is schema-stable conversation analysis you control.
- [Capacity Planning Lags Because Sales Data Misses the Act of Selling](https://semarize.com/resources/blog/capacity-planning-lags-missing-act-of-selling-data.md): Sales capacity models built on CRM events are structurally late. Stage labels and activity counts record what happened to deals, not what was happening inside them. The missing ingredient isn't more pipeline data - it's structured signals from selling conversations that show whether buyers actually understood, committed, and progressed.
- [Churn Risk Shows Up in CS Calls Before It Shows Up in Health Scores](https://semarize.com/resources/blog/churn-risk-signal-extraction-from-cs-calls.md): Most churn detection models catch the consequences - usage drops, NPS decline, support spikes - after the customer has already started disengaging. The predictive signals are in CS call recordings: escalation language, stakeholder engagement changes, absent expansion mentions, deferred follow-through. Knowledge-grounded extraction turns these into signals calibrated to your definitions - making early intervention possible in a way generic extraction can't.
- [Conversation Data Warehouse: Getting Consistent Call Fields Into BigQuery, Snowflake, and Databricks](https://semarize.com/resources/blog/conversation-data-warehouse-typed-call-fields.md): BI teams can't query transcripts. They can't join AI summaries to CRM objects. To make conversation data useful for analytics, it needs to arrive as consistent typed fields - booleans, scores, text fields, lists - with join keys that connect calls to opportunities, accounts, and contacts. This is the pipeline, the schema, and the governance model that makes sales call analytics possible in your warehouse.
- [Conversation Intelligence Doesn't Fail on Calls. It Fails on Knowledge.](https://semarize.com/resources/blog/conversation-intelligence-fails-on-knowledge-not-calls.md): Early CI tools were built on ML classifiers - talk ratios, question counts, keyword detection. LLMs changed what's possible. But they introduced a new risk: model knowledge. When scoring runs against what the AI infers from training rather than your pricing, ICP criteria, and qualification playbooks, outputs are plausible and wrong.
- [Conversation Intelligence for Developers: Don't Build a Fragile Pipeline, Don't Buy a Black Box](https://semarize.com/resources/blog/api-first-conversation-intelligence-structured-json.md): Most teams don't fail to add conversation intelligence because the model is bad; they fail because the integration is fragile and unstructured. The fix isn't a better LLM pipeline or a platform API you can't control. It's a layer that takes a transcript, runs it against a versioned Kit, and returns deterministic typed JSON you can test, version, and route into your product.
- [Conversation Intelligence for Sales Enablement: Stop Measuring Deal Signals, Start Measuring Skill Lift](https://semarize.com/resources/blog/conversation-intelligence-sales-enablement-skill-lift.md): Most enablement teams measure the wrong thing. Deal signals tell you whether a deal progressed. Skill signals tell you whether a rep developed a capability. The two require different schemas, different measurement windows, and a different definition of what you are trying to prove. Here is how to design for skill lift specifically.
- [Conversation Intelligence Isn't Enablement Analytics. Here's What Is.](https://semarize.com/resources/blog/conversation-intelligence-isnt-enablement-analytics.md): Sales enablement teams buy conversation intelligence to measure coaching impact, then find the dashboards don't produce what they need: consistent rubric scoring, queryable time-series data, and before-and-after skill lift metrics. Visibility into calls and measurement of skill development are different problems - and most CI tools only solve the first one.
- [Conversation Intelligence Produces the Signals. Outcomes Depend on What You Build With Them.](https://semarize.com/resources/blog/conversation-intelligence-wont-fix-forecasts-signals-to-workflow.md): CI vendors sell outcomes - better forecasts, improved coaching, higher win rates. The outcome claims are accurate for teams that wire CI signals into their downstream workflows. For teams that don't, the dashboards fill up and the outcomes don't move. The gap between running CI and seeing results is always an implementation gap, not a vendor gap.
- [CRM Enrichment From Sales Calls: The RevOps Data Ops Playbook](https://semarize.com/resources/blog/crm-enrichment-from-sales-calls-structured-json-playbook.md): Most CRM enrichment stalls at 30% field coverage because the output is unstructured - reps updating from memory, summaries stored as notes. The fix is a structured extraction pipeline: transcript to consistent fields to CRM to automation triggers. This playbook covers the schema, the routing, and the implementation in Salesforce and HubSpot.
- [Gong Captures the Transcript. Here’s What It Can’t Score.](https://semarize.com/resources/blog/gong-to-json-extract-revops-signals-without-pipeline.md): Gong’s scoring runs against a fixed model — you can’t attach your product documentation, rate card, or qualification playbook to its evaluation layer. For four evaluations that matter — product accuracy, pricing audit, methodology A/B testing, and deal readiness scoring — knowledge grounding and KB isolation are the only architecture that works.
- [GTM Engineering in 2026: What Revenue Data Engineering Actually Means](https://semarize.com/resources/blog/gtm-engineering-2026-revenue-data-engineering.md): GTM engineering has matured on the workflow layer. The constraint has moved. Most teams building AI-augmented revenue pipelines are hitting a data problem: the conversation layer where deals actually progress is still unstructured, inconsistent, and inaccessible to the systems that need it. That is what revenue data engineering is for in 2026.
- [Introducing the Semarize MCP](https://semarize.com/resources/blog/introducing-the-semarize-mcp.md): Today we're shipping the Semarize MCP. Connect Claude, Codex, or any MCP-compatible AI tool to your workspace and build evaluation schemas from inside a conversation: create Bricks, draft Kits, attach knowledge bases, and publish, without leaving the tool you're already working in.
- [MEDDICC Without the Admin: Deterministic Scoring for Every Discovery Call](https://semarize.com/resources/blog/meddicc-scoring-stale-data-transcripts-deterministic.md): Most MEDDICC data is stale before it reaches CRM. Reps update fields from memory after the call, introducing timing gaps and sampling bias that make qualification scores unreliable. Extracting MEDDICC signals directly from transcripts fixes the data freshness problem that better training never will.
- [Overhiring Is a Measurement Failure, Not a Hiring Strategy](https://semarize.com/resources/blog/overhiring-is-a-measurement-failure.md): Sales teams don't overhire because of poor judgment. They overhire because CRM-driven capacity models are built on stage labels and activity counts - data that can't reveal whether buyers are actually progressing. By the time deal reality becomes visible, headcount decisions have already been made.
- [Sales is human. Sales data is not.](https://semarize.com/resources/blog/sales-is-human-sales-data-is-not.md): CRM data captures events - stage changes, activity counts, timestamps. It doesn't capture the human act of selling. The evidence that explains why deals move or stall lives in conversations, not in fields a rep updated.
- [Start Evaluating Agents the Way You Should Be Evaluating Humans](https://semarize.com/resources/blog/start-evaluating-agents-the-way-you-should-be-evaluating-humans.md): If you're running structured evaluation on every human rep conversation, your AI agent conversations should go through the same contract. Vendor metrics tell you how the agent performed against the vendor's model of a good interaction. Your evaluation standards are different. The same deterministic Kit you use for human reps applies directly to AI agent conversations: same schema, same grounded Bricks, same structured JSON output at 100% of production volume.
- [Stop Running Win/Loss Surveys. Start Capturing Deal Signals From Calls.](https://semarize.com/resources/blog/stop-running-win-loss-surveys-start-capturing-deal-signals-from-calls.md): Win/loss surveys have a structural timing problem: they collect buyer memory after the outcome, not the decision inputs during the deal. Competitor mentions, pricing responses, and stakeholder dynamics exist in call recordings as they happen. Extracting them as structured signals makes win/loss real-time - and far more useful for deal coaching and pipeline risk.
- [The Best APIs for Building Internal Sales Tools in 2026](https://semarize.com/resources/blog/best-apis-internal-sales-tools-2026.md): The GTM engineering stack for internal sales tooling is well settled in 2026. Here is what each layer looks like, which tools are worth building around, and what RevOps and enablement teams are actually assembling from them.
- [What Conversation Intelligence Is Actually Missing and How to Fill the Gap](https://semarize.com/resources/blog/what-conversation-intelligence-is-actually-missing-and-how-to-fill-the-gap.md): Most teams already have conversation data. The problem isn't volume - it's that transcripts sitting in Zoom Cloud or a shared Drive folder are locked in text no system in your stack can read. Semarize turns what was said into structured JSON your CRM, BI, and automations can consume directly.
- [What is a Conversational Intelligence API?](https://semarize.com/resources/blog/what-is-a-conversational-intelligence-api.md): Conversational intelligence gets applied to three very different things - deal intelligence, note-taking, and pattern-level analysis. Only one produces data your systems can act on. Here's what a CI API actually does and how the shift away from full-platform solutions is changing what's possible.
- [What Is a Conversational Intelligence API? (And Why It's Not an AI Note-Taker)](https://semarize.com/resources/blog/what-is-a-conversational-intelligence-api-not-an-ai-note-taker.md): Most tools that call themselves conversational intelligence produce prose summaries for humans to read. A conversational intelligence API produces structured data for systems to consume directly, and that difference in output format determines everything about what you can build with the data.
- [Where Vibe Coding Actually Makes Sense for Internal Teams](https://semarize.com/resources/blog/where-vibe-coding-makes-sense-internal-teams.md): AI coding has moved faster than most of the discourse around it. The question is no longer whether you can build with AI; it’s where to direct the effort, and the people best placed to answer that are the ones already closest to the problem.
- [Why Conversation Intelligence Doesn't Drive Behavioural Change (and What Does)](https://semarize.com/resources/blog/conversation-intelligence-behavioural-change.md): Eighteen months into a CI implementation, many teams find that call scores have improved but win rates haven't moved. The data is there. The dashboards are running. The coaching is happening. What's missing is the step where insight becomes a different behaviour in the next conversation - and CI alone doesn't close that gap.
- [Why I've built Semarize.](https://semarize.com/resources/blog/why-ive-built-semarize.md): It's about time we looked at our conversations through a more scientific lens - This is why I've built Semarize, what it's for and what I want it to help people do.
- [Alex Handsaker](https://semarize.com/resources/blog/authors/alex-handsaker.md): Alex spent most of his career in tech sales and revenue enablement, where he saw a consistent gap - the most important data in go-to-market lived in conversations, but couldn't be structured or used. Semarize is built to change that: turning conversations into something systems can actually operate on.

## Company
- [About Semarize](https://semarize.com/about.md): Company and product information for Semarize.
- [Legal](https://semarize.com/legal.md): Terms, privacy policy, acceptable use policy, and service levels for Semarize.