Performance. Scale. Reliability—Engineered.
KPI99 is an AI-Augmented Performance Engineering consultancy supporting mission-critical systems in scale-critical environments. We specialize in Performance. Scale. Reliability—Engineered.
Our team of performance architects applies proven enterprise methodologies, AI-assisted diagnostics, and proprietary assessment frameworks, including our Performance Pressure Index framework (PPI-F), to identify performance limits, reduce latency, prevent outages, and improve infrastructure efficiency before issues impact customers or regulators.
Our team of architects brings architect-level experience supporting large-scale, regulated platforms where performance, reliability, and predictability are business-critical.
We have worked across environments including financial services, large data platforms, event-driven architectures, and cloud-based enterprise systems operating under strict SLA requirements. This experience has informed the development of our proprietary assessment frameworks, including the Performance Pressure Index framework (PPI-F) with integrated AI capabilities: ML-based anomaly detection (Performance), predictive capacity forecasting (Predictability), workload behavioral segmentation (Intelligence), and AI-driven cost modeling (Financial).
KPI99 follows a structured, evidence-driven performance architecture methodology refined in large enterprise environments by architects with experience in system design at scale.
Each engagement combines application-level analysis, AI-assisted anomaly detection, predictive capacity modeling, and infrastructure saturation analysis to provide clear, actionable insight for technical and executive stakeholders. Our approach incorporates the Performance Pressure Index framework (PPI-F) with AI-enhanced predictive modeling to systematically quantify performance pressure, forecast capacity curves, and prioritize interventions.
A systematic, data-driven approach to performance engineering that delivers measurable results.
Comprehensive system analysis using APM tools, profiling, and load testing to establish baseline performance metrics and identify constraints. We apply our Performance Pressure Index framework (PPI-F) with AI-assisted anomaly detection to systematically assess system performance pressure and identify behavioral patterns.
Deep-dive investigation into application code, JVM tuning, database queries, network I/O, and infrastructure configuration to pinpoint root causes. AI-enhanced workload behavior modeling helps identify distributed system bottlenecks, including Spark executor skew and cluster efficiency issues.
AI-driven mathematical modeling of system capacity under various load scenarios, including peak traffic, growth projections, and failure modes. Predictive models forecast capacity curves and cost-to-serve trajectories, enabling proactive scaling decisions.
Targeted improvements to code, configuration, and architecture with validation through controlled load testing and performance regression analysis. AI-enabled governance provides automated threshold monitoring and cost guardrails to prevent drift.
Production validation, establishment of performance SLAs/SLOs, and implementation of AI-powered monitoring dashboards for ongoing visibility. Continuous model refinement through recurring advisory subscriptions ensures predictive accuracy.
Architect-level expertise across the full performance engineering stack, from application code to infrastructure, with the ability to design and optimize complex systems at enterprise scale.
KPI99 integrates AI and machine learning to enhance performance engineering capabilities, focusing on enterprise distributed systems including Spark, EMR on EKS, and JVM platforms.
ML-based anomaly detection and workload behavior modeling to identify performance issues before they impact production.
Forecast demand trajectories and simulate tier multiplier scenarios to optimize infrastructure spend and scaling decisions.
AI-powered detection of Spark executor skew, cluster efficiency issues, and workload distribution patterns in distributed systems.
Automated cost guardrails, threshold drift detection, and continuous model refinement to maintain performance standards.
We focus delivery on three cross-cutting initiatives that align performance engineering with business outcomes.
Optimize infrastructure utilization and cost through AI-driven analysis, right-sizing, and workload placement—reducing waste while preserving performance and reliability.
Forecast spend and usage trends before they hit the budget. ML-based early-warning systems surface cost drivers and anomalies so you can act ahead of overruns.
Third-party, evidence-based review of cloud and infrastructure spend. Delivers unbiased benchmarks, waste identification, and defensible recommendations for finance and leadership.
Proven experience across industries where performance directly impacts business outcomes.
Learn how KPI99 helps organizations eliminate performance constraints and scale efficiently.
The following case studies reflect real enterprise performance engagements conducted under NDA. Metrics are anonymized but technically representative.
The platform experienced hyper-growth in billing and usage events, scaling from ~475K events/day (2023) to 20M+ max daily events (Oct 2025). Growth introduced highly variable tenant usage patterns and risk of saturation at ingestion, entitlement, and query layers.
Throughput was concentrated into 12-14 hour active windows and 3-5 hour peak periods. Without explicit peak modeling, the system risked latency spikes, downstream backpressure and missed SLAs during regional demand surges.
As daily and hourly usage volumes increased, ingestion throughput appeared capped at ~2.5M events per hour. Detailed analysis revealed Spark execution performance remained stable; the dominant source of delay was job queue wait time, not processing time.
As usage scaled, entitlement processing and UI performance faced long-tail latency growth, increased Spark cluster costs and risk to customer-facing response times.
Our team has delivered measurable improvements across enterprise environments.
KPI99 operates as a focused consulting practice delivering architect-level performance engineering expertise.
Engagements are led by experienced performance architects with enterprise backgrounds, ensuring direct access to deep technical capability and system design expertise at scale without the overhead of large consulting teams.
KPI99 regularly supports delivery partners by providing specialized performance and capacity expertise during high-impact initiatives.
Our role is to reduce delivery risk, strengthen outcomes, and increase confidence during migrations, scale events, and performance-sensitive programs.
Get in touch to discuss your performance engineering needs. Our team will review your requirements and provide a tailored assessment of how we can help optimize your systems.