STROT

Structured Task Reasoning and Output Transformation

NewIntroducing Cortex

Enterprise Knowledge Personalization. Ask. Build. Deploy.

The market gap

Every organization today faces the same challenge: endless data operations work. Building pipelines, running reports, monitoring metrics, generating alerts. The work never stops, and the backlog keeps growing.

Teams have tried two approaches. Both are fundamentally broken.

Traditional data tools: Code everything

Every workflow requires engineering resources. Business teams submit tickets and wait weeks for development. Each change means another sprint, another priority discussion, another dependency on scarce technical talent. The engineering backlog grows faster than teams can hire.

AI agents: Promise automation, deliver chaos

Pure AI agent platforms look magical in demos. Natural language, instant results, no coding required. But in production? Non-deterministic outputs. Hallucinations in critical business processes. No audit trails for compliance teams. What works Tuesday fails Wednesday with the same input. Operations teams refuse to deploy them.

External tools: Friction by design

Companies force users to leave their app, log into a separate analytics platform, learn new interfaces, and manually query data. Every question requires context switching. Business teams avoid asking questions because the friction is too high. Data sits unused while decisions are made on intuition instead of insights.

Solution that STROT brings

The real problem isn't choosing between speed and reliability. It's that existing tools force this false choice.

Organizations need workflows that business teams can build without waiting for engineering, but that operations teams can trust to run in production. AI-assisted design for speed and accessibility. Deterministic execution for reliability and compliance.

This is what STROT delivers: the intelligence and ease of AI agents during design, with the reliability and auditability of traditional pipelines in production. Business users design workflows in hours using natural language and visual tools. Those workflows compile to production-grade pipelines with guaranteed deterministic execution and complete audit trails.

Embedded analytics: Zero friction

Drop a simple embed code into your app, and users get instant access to chat-based analytics without leaving your interface. No separate logins. No external tools. Just natural language queries that connect directly to your data.

<script src="https://strot.ai/embed.js"></script>
<div id="strot-assistant" data-key="sk_live_xyz123"></div>

API keys automatically discover schema and enable chat. No manual "create data sources" step. Natural language is the interface—no SQL required.

No more choosing between fast and reliable. No more engineering bottlenecks. No more AI systems that break in production. No more forcing users to external tools.

Compiled AI for data operations

STROT's core insight is deceptively simple: Use AI as a design tool, not a runtime dependency.

Just as software developers write high-level code that compiles to efficient machine code, STROT allows business users to describe data workflows in natural language that compile to optimized, production-ready pipelines. You design with AI assistance, but execute with guaranteed reliability.

Design time: AI assists (fast, intuitive, build workflows without coding)

Runtime: Native execution (trusted for production use, auditable, cost-effective)

Unlike tools that only solve one piece of the puzzle, STROT provides a unified platform for the complete data operations lifecycle:

Explore

Chat with your data using natural language. Ask questions, investigate trends, and understand your business without depending on technical teams.

Analyze

Build sophisticated analytics workflows combining data transformations, statistical models, and AI-powered insights without engineering support.

Automate

Design visual workflows that run on schedules, triggers, or events. Monitor, alert, and respond to changes automatically.

Activate

Sync insights to marketing tools, CRMs, dashboards, Slack, email, wherever your teams need them. Real-time personalization and audience segmentation at scale.

Governance and compliance built-in

Every workflow execution is fully auditable with complete data lineage. STROT automatically tracks:

  • Who created and modified each workflow
  • What transformations were applied to the data
  • When workflows ran and what results they produced
  • Why decisions were made (for AI-assisted workflows, reasoning is preserved)

This audit trail meets compliance requirements for SOC 2, HIPAA, GDPR, and financial services regulations. Every execution is deterministic: same input always produces the same output. This makes it suitable for regulated industries where non-deterministic AI systems cannot be deployed.

Built on proven research

STROT is built on research in structured prompting and feedback-guided reasoning. We treat language models as modular agents within controlled reasoning loops rather than one-shot oracles. This approach mirrors how analysts work: inspecting data, forming hypotheses, and adapting based on results.

The result is AI that assists intelligently during design while ensuring production workflows run with complete reliability and transparency.

Analytics, Activation, Personalization: Unified

Advanced analytics

Chat with your data to explore trends and anomalies. Build sophisticated analytical workflows combining data transformations, statistical models, and AI-powered insights.

From exploratory analysis to automated reporting, dashboards, and alerts. All in one platform with full audit trails for compliance.

Data activation at scale

Sync insights to marketing tools, CRMs, email platforms, Slack, and data warehouses. Real-time audience segmentation and campaign orchestration.

Unlike reverse-ETL tools, STROT adds intelligent processing like sentiment analysis, predictive scoring, and anomaly detection before activation.

Intelligent personalization

AI-powered customer segmentation based on behavior, preferences, and predictive models. Deliver personalized experiences across email, web, mobile, and advertising platforms.

Build complex personalization logic visually with no coding required. Test variations, measure impact, and iterate in hours instead of weeks.

Production reliability & governance

Deterministic execution means same input always produces the same output. No hallucinations in production workflows. Fully auditable with complete data lineage.

Meets SOC 2, HIPAA, GDPR, and financial services compliance requirements. Trusted for regulated industries where reliability is non-negotiable.

10x faster iteration

Build workflows without coding using natural language and visual builders. Business analysts, marketers, and researchers ship independently without engineering bottlenecks.

From idea to production in hours instead of weeks. Immediate feedback during design, one-click deployment to production environments.

Predictable economics

AI used once at design time (pennies). Execution costs are pure compute (fractions of a cent). Unlimited runs with predictable costs.

Data stays in your infrastructure with processing happening locally or in your cloud. Only metadata is shared with AI during design, meeting security requirements of conservative enterprises.

Built for production

Emphasis on human-AI collaboration. Instead of focusing solely on making fully autonomous AI systems, we build systems where AI assists at design time and deterministic execution handles production workloads.

Infrastructure quality as a top priority. Analytics productivity depends on reliability, efficiency, and ease of use. We build things correctly for the long haul, to maximize both productivity and security, rather than taking shortcuts.

Built for teams who need reliability

CXOs and executives

Want to chat with data as a private assistant to get instant answers. Need strategic insights without waiting for analyst reports or dashboards.

Business analysts

Blocked by engineering backlogs. Need to build data workflows independently while maintaining quality and reliability standards.

Researchers

Need reproducible data pipelines for publications. Want to spend time on analysis, not debugging ETL scripts and data quality issues.

Marketing teams

Need real-time audience segmentation and data activation. Want to test campaigns with fresh data without waiting on engineering resources.

Financial analysts

Require accurate, repeatable reporting for forecasting and risk modeling. Need audit trails for regulatory compliance and internal controls.

Healthcare analytics

Must meet HIPAA requirements with full data lineage. Need deterministic workflows for patient outcomes analysis and clinical trials reporting.

Cyber risk analysts

Analyze threat intelligence and security events at scale. Need fast iteration on detection rules with complete audit history for incident response.

Insurance underwriters

Combine claims data, risk models, and external sources for accurate pricing. Need repeatable workflows that regulators can audit and verify.

Sports analytics teams

Process real-time player performance and game statistics. Need automated pipelines for scouting reports and performance dashboards during game time.

Real-world impact

Healthcare provider automates patient outcomes reporting

Mid-sized hospital network • 500+ beds • Regulatory compliance

Challenge

Analytics team spent 40+ hours per month manually extracting patient data from EHR systems, transforming it for HIPAA-compliant reporting, and generating outcomes reports for clinical quality committees. Each report required 3-4 days of SQL scripting and validation.

Solution

Built visual workflows in Cortex connecting EHR databases, applying standardized transformations, and automating report generation. Designed in 2 hours, compiled to deterministic pipelines with full audit trails for compliance teams.

Results

  • 95% time reduction: From 40 hours/month to 2 hours for monitoring and updates
  • 100% audit compliance: Every transformation documented and traceable for regulators
  • Zero data errors: Deterministic execution eliminated manual mistakes in reporting
  • $120K annual savings: Freed analyst time for higher-value clinical research projects

Insurance company scales fraud detection workflows

Regional insurer • $2B+ in annual premiums • Risk analytics

Challenge

Fraud analysts needed to cross-reference claims data with external databases, apply ML risk scoring models, and flag suspicious patterns. Each new detection rule required 2-3 weeks of engineering work. Backlog of 40+ detection ideas awaiting implementation.

Solution

Analysts designed fraud detection workflows visually using Cortex, combining database queries, API calls to third-party data providers, and ML model scoring. IT reviewed and deployed workflows with one-click production deployment.

Results

  • 10x faster iteration: New detection rules deployed in hours instead of weeks
  • $4.2M fraud prevented: Cleared backlog and deployed 35 new detection workflows in first quarter
  • Regulatory ready: Full audit trails for all automated decisions, meeting state compliance requirements
  • Team empowerment: Fraud analysts now build and deploy independently, freeing engineering for core infrastructure

E-commerce retailer personalizes customer experiences at scale

Online retailer • 2M+ active customers • Marketing automation

Challenge

Marketing team wanted to segment customers based on purchase history, browsing behavior, and predictive churn models to personalize email campaigns. Engineering queue had 6-month backlog. Campaigns ran with stale data and missed revenue opportunities.

Solution

Marketing ops built audience segmentation workflows in Cortex, combining warehouse queries, ML predictions, and real-time behavioral triggers. Automated sync to email platform and A/B testing framework. Non-technical marketers designed and deployed workflows independently.

Results

  • 32% increase in email revenue: Fresher data and better segmentation drove conversions
  • Daily updates instead of weekly: Campaigns now react to customer behavior within hours
  • 15 new segments launched: Marketing team shipped in 2 weeks what previously took 6 months
  • Cost efficiency: Unlimited executions at predictable compute costs, vs. expensive per-run AI agent fees

SaaS company reduces customer churn with predictive analytics

B2B SaaS platform • 50K+ customers • Retention focus

Challenge

Customer success team needed to identify at-risk accounts before cancellation. Data scattered across product usage, support tickets, billing, and NPS surveys. No unified view to predict churn or prioritize outreach.

Solution

Built churn prediction workflows combining usage patterns, support interactions, payment history, and sentiment analysis. Chat-based interface lets CS managers ask "Which enterprise accounts are at risk this month?" and get instant, actionable insights with reasoning.

Results

  • 24% churn reduction: Proactive outreach to at-risk accounts before cancellation
  • Conversational insights: Managers chat with data instead of building dashboards
  • Daily predictions: Automated scoring updates every 24 hours with fresh data
  • $2.8M ARR saved: Retained high-value customers through targeted interventions

Investment bank automates credit risk assessments

Regional bank • $15B+ assets • Risk modeling

Challenge

Risk analysts manually aggregated borrower financials, market indicators, and credit bureau data for loan approvals. Each assessment took 4-6 hours. Regulatory stress tests required weeks to complete. No way to chat with historical data for scenario analysis.

Solution

Created chat-based risk investigation workflows. Analysts ask conversational questions like "Show me all commercial loans with LTV above 80% in declining markets" and get instant analysis. Automated stress testing pipelines run regulatory scenarios with full audit trails.

Results

  • 85% faster assessments: Credit risk analysis reduced from hours to minutes
  • Natural language queries: Risk officers explore portfolios conversationally without SQL
  • Regulatory compliance: Every decision fully documented for auditors and examiners
  • Scenario flexibility: Run hundreds of stress test variations in minutes vs. weeks

City planning department analyzes urban development with chat

Municipal government • 500K+ residents • Smart city initiative

Challenge

Urban planners needed to analyze zoning data, demographics, infrastructure capacity, and environmental impact across multiple GIS layers. Complex spatial queries required GIS specialists. Decision-makers couldn't explore data independently for policy decisions.

Solution

Built chat-based GIS investigation platform. Planners ask questions like "Find residential zones within 500m of new transit stations with population growth above city average" and receive maps, statistics, and insights instantly. AI translates natural language to PostGIS spatial queries.

Results

  • 10x faster analysis: Complex spatial investigations completed in minutes, not days
  • Non-technical access: City council members explore GIS data without specialized training
  • Evidence-based policy: Data-driven zoning decisions backed by spatial analytics
  • Public transparency: Reproducible analysis workflows for community review and feedback

Learn by Doing

Research and product co-design. Products enable iterative learning through deployment. We focus on solving real problems for data teams in regulated industries and cost-conscious enterprises.

Measure what truly matters. We focus on understanding how our systems create genuine value in the real world. Success is measured by production deployments, not prototype demos. We optimize for reliability and cost-effectiveness, not just capability.