Real-Time Revenue Intelligence
SingleStore enables SalesTech platforms to run millisecond analytics with high concurrency on AI-ready data, so every forecast, recommendation, and workflow continuously operates on the latest revenue insights.
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Trusted by leading SalesTech platforms
Sales engagement, forecasting, and conversation intelligence platforms are no longer back-office reporting tools. Buyers expect live pipeline health, instant coaching insights, and in-the-moment recommendations. Batch analytics introduces delays between seller action and system insights, reducing platform value and delaying seller impact.
AI copilots, next-best-action engines, and automated deal inspection have become standard capabilities within modern SalesTech platforms. As AI moves from offline experimentation into production workflows, it must process and correlate fresh revenue insights in real-time. Stale or fragmented context reduces model accuracy and erodes user trust.
Modern SalesTech platforms ingest millions of daily events: emails, calls, meetings, CRM updates, product usage signals. Thousands of reps, managers, and AI agents access the same system concurrently, generating heavy simultaneous load. Architectures designed for isolated analytics struggle to sustain this dual pressure.
Fragmented data creates latency and reduces trust
Sales activity, CRM records, enrichment data, and usage telemetry often live in separate systems, forcing pipelines and synchronization jobs that introduce delays and inconsistencies.
What’s needed:
A unified data foundation where operational and analytical workloads share the same live dataset without replication or lag.
Batch pipelines erode AI accuracy and trust
Forecasting models and recommendation engines frequently depend on nightly refreshes, meaning AI decisions are grounded in yesterday’s pipeline reality.
What’s needed:
Continuous ingest and real-time queryability so AI models operate over current, governed revenue data at the moment of decision.
Concurrency bottlenecks restrict platform scalability
High seller concurrency combined with dashboard refreshes and AI workloads generates unpredictable latency spikes in traditional architectures.
What’s needed:
Linear scalability with consistent low-latency performance under thousands of concurrent users and AI agents.
Fragmented systems drive cost and operational risk
Maintaining transactional databases, warehouses, caches, and vector stores adds operational complexity and increases governance risk exposure.
What’s needed:
A single, ACID-compliant engine capable of handling transactions, analytics, and AI workloads together.
Governance and auditability cannot be afterthoughts
Revenue forecasts and performance metrics drive executive decision-making. Inconsistent data copies and siloed systems complicate auditing,compliance, and regulatory reporting.
What’s needed:
A secure, governed platform with role-based access controls and consistent data lineage across all workloads.
Unified transactions + analytics
SingleStore runs operational writes and analytical queries in a single data platform, eliminating ETL delays and enabling real-time revenue visibility across pipeline, activity, and engagement signals.
Rapid ingest at scale
Ingest millions of sales events per second and make them instantly queryable - powering live dashboards, scoring engines, and in-product AI workflows.
High concurrency without performance loss
Support thousands of sellers, managers, dashboards, and AI agents simultaneously querying with consistent millisecond response times.
ACID-correct + Enterprise ready
Maintain transactional correctness for revenue-critical workflows while delivering high-performance analytics at scale - no compromise between speed and safety.
AI-ready foundation
Run vector search, relational joins, and complex queries in a single engine so copilots, forecasting models, and next-best-action systems operate on live, unified data.
Real-time pipeline health
Sales leaders need immediate visibility into deal progression, risk signals, and coverage gaps. Traditional batch reporting introduces delays, leaving stale insights. With a unified real-time engine, pipeline metrics update instantly enabling proactive coaching, risk mitigation, and more accurate forecasting.
AI sales copilots
AI copilots assist reps with next-best actions, messaging suggestions, and deal strategy. They operate on live CRM data, engagement history, enrichment signals, and historical outcomes. A unified foundation ensures every AI recommendation reflects the latest context.
Conversation intelligence at scale
Call transcripts, sentiment analysis, keyword extraction, and deal scoring generate high-volume, semi-structured data. Real-time ingestion and analytics enable platforms to surface insights immediately after each call, improving coaching impact and customer experience.
Turning high-volume website data into real-time action
ZoomInfo’s Websites product delivers near real-time visitor intelligence at massive scale. As growth accelerated, BigQuery couldn’t keep up on latency, concurrency, or cost. The team needed a faster, scalable analytics engine that could support real-time updates and future expansion—without heavy rework. They chose SingleStore for distributed scale, fast ingestion, flexible cloud deployment, and lower total cost.
Key outcomes / impact
24× faster response times overall
P95 list queries: 26s → ~1s (~25× faster)
Dashboard queries: ~5s → sub-millisecond
~75% lower TCO (down to ~1/4 of projected cost)
Storage reduced from 8.5 TB to 5 TB
Ready to support 6× growth
“With BigQuery, our P95 latency was 26 seconds—and with SingleStore it came down to like 1 second.” - Ganesh Srinivassingh, Engineering Manager, ZoomInfo
Powering real-time revenue intelligence for modern sales teams
Outreach helps sellers execute structured outreach and analyze conversations in real time. As the platform expanded into conversation intelligence and AI-driven workflows, the team needed faster, simpler analytics to support drill-down insights from forecast to deal to call. SingleStore helped streamline the data layer, reduce latency, and deliver fresh insights instantly to revenue leaders.
Key outcomes / impact
Analytics stack simplified
Fresh, instantaneous access to revenue data
Query latency reduced “tremendously”
Enables deep drill-down from forecast → deal → conversation
“Being able to get data that’s fresh, that’s instantaneous—you reduced our query latency like tremendously.” -Abhijit Mitra, CEO, Outreach
Unifying AI + analytics + revenue intelligence at scale
6sense processes massive volumes of behavioral, CRM, and advertising data to power AI-driven revenue insights for B2B teams. Rapid growth and expanding AI capabilities demanded a unified data layer that could support real-time user experiences and advanced machine learning workloads simultaneously. SingleStore became the consolidation point - bringing performance, scale, and AI readiness together.
Key Impact
Tens of terabytes managed with 27 months of retained history
Consolidated multiple legacy databases into one layer
Improved query performance across customer-facing UIs
Reduced total cost of ownership
Powered AI features including real-time summaries and vector search
“We wanted all personas to use data from the same layer—with no discrepancy—and do it as fast as possible. SingleStore gave us that foundation.” - Premal Shah, Co-Founder & SVP Engineering and Infrastructure, 6sense
Faster decisions
Move from delayed reporting to instant revenue visibility. Empower sellers and leaders to act on pipeline risk, opportunity signals, and AI insights as they emerge.
Platform differentiation
Deliver truly real-time dashboards, recommendations, and forecasting that competitors built on batch architectures cannot match.
Architectural simplification
Consolidate transactional databases, warehouses, and specialized AI stores into a unified, scalable platform - reducing cost and operational overhead.
AI monetization at scale
Confidently embed AI across your product portfolio, knowing models operate on fresh, consistent data under high concurrency.
Power the next generation of revenue platforms
Modern SalesTech demands live insight, embedded AI, and enterprise-scale performance.