Stovell AI
AI Based SaaS Vendor
Stovell AI is a predictive analytics company building forward-looking pricing systems for global energy providers and financial asset managers. By blending real-world expertise with proprietary machine learning models, Stovell helps clients anticipate market behavior and uncover pricing inefficiencies before they’re visible to the rest of the market.
To support their growth, Stovell needed an engineering partner who could build a scalable, cloud-based AI platform tailored for both enterprise usability and institutional-grade insights. Azumo joined as a long-term development partner to help bring this vision to life—engineering production-ready AI models, building modern SaaS infrastructure, and embedding powerful forecasting tools into user-friendly interfaces.
The Challenge
In volatile energy and financial markets, timing is everything. Stovell’s internal teams of data scientists and quantitative strategists had developed advanced signal extraction methods—but transforming these insights into scalable software required deep engineering capacity.
One challenge was enabling real-time pricing forecasts that would allow clients to react daily to competitive shifts. Stovell’s AI needed to do more than predict—it had to model how customers and competitors would respond to price changes, with logic sophisticated enough for energy traders and hedge fund CIOs alike.
Seamless delivery was equally critical. Clients needed a solution that could integrate with their existing workflows without additional IT overhead. This meant building a true SaaS product: one that delivered structured outputs with no deployment friction. For financial clients, the bar was even higher—the platform needed to support systematic equity strategies and be flexible enough to generate customized short exposures, overlays, and forward-looking risk signals.
We’ve been working with Azumo since our founding. Their team has been great to work with. We built out a massive AI based data platform with their help. They can handle just about anything.
The Solution
Azumo helped architect and develop a fully integrated AI platform tailored to Stovell’s clients across industries. Working in tandem with Stovell’s domain experts, Azumo built proprietary systems and interfaces that made advanced predictions accessible, actionable, and performant at scale.
The partnership began with the development of Market Vision, Stovell’s core dynamic prediction engine. This system provides daily, regionally-tuned pricing forecasts that allow energy clients to optimize their competitive positioning—automatically adjusting to new signals and price shifts in real time.
To support institutional finance clients, Azumo co-developed a suite of specialized tools under the Financial AI Suite, including Night Vision, XVision, and Regime Vision—each targeting specific alpha-generation workflows.
Systematic Short Exposure
One of the flagship tools was Night Vision, a 100% short-side exposure engine that generates pre-formatted, daily equity tranches tailored to a client’s risk parameters and portfolio universe. The model, live since 2017, consistently delivered alpha across market cycles while requiring only minimal daily operational effort.
Figure 1. Night Vision Live Alpha vs. S&P500
The Night Vision shorting system consistently outperformed S&P500 benchmarks across a 12-month period, delivering robust short-side alpha with minimal daily input. Results were delivered as pre-formatted CSVs for OMS-ready integration.
Borrow Rate Forecasting
Azumo also supported the development of XVision, a borrow rate forecasting tool designed for equity finance desks. The system forecasts short-term changes in borrow rates with probabilistic indicators and share-loan dynamics, enabling borrow desks to optimize match book profitability and gain market share. XVision is delivered via a zero-IT SaaS interface, with live signal tracking built directly into the platform.
Figure 2. XVision Borrow Rate Forecasting Interface
XVision visualizes predicted borrow rate changes, tracking current shares on loan, price data, and 5-day forward movement probabilities—empowering borrow desks with forward-looking trade signals and lending risk management.
Early Bull/Bear Inflections in Market Trend
To support broader portfolio strategy, Azumo helped launch Regime Vision, a tool designed to identify early trend inflections and risk regime shifts across sectors and benchmarks. Portfolio managers used this system to tactically adjust exposure and improve risk-adjusted returns—based on daily AI-driven signal updates. The interface tracked live signal accuracy and integrated seamlessly into workflows.
Figure 3. Regime Vision: Risk Inflection Detection and Optimization Signal.
The Regime Vision system highlighted bullish and bearish positioning across client watchlists and benchmarks, surfacing inflections in underlying risk regimes with zero IT lift.
Results
The collaboration between Stovell and Azumo led to tangible outcomes across both product and business dimensions:
- Fuel Pricing Optimization: Stovell’s Market Vision allowed energy clients to proactively adjust prices by region, responding to competitor actions and market volatility with confidence.
- Superior Short-Side Performance: Night Vision helped institutional clients generate consistent alpha through automated, daily hedge exposures—freeing investment teams to focus on discretionary strategies.
- Equity Lending Intelligence: XVision equipped borrow desks with a predictive edge, boosting utilization and improving profitability on hard-to-borrow names.
- Portfolio-Level Risk Optimization: Regime Vision empowered portfolio managers to react early to risk regime shifts—sharpening their exposure decisions and improving risk-adjusted returns.
Stovell AI’s partnership with Azumo helped transform advanced signal research into enterprise-grade financial and energy forecasting tools. From platform architecture to algorithmic execution, Azumo’s engineering team played a central role in delivering scalable, intelligent software that gives Stovell’s clients a consistent edge.
This case study illustrates how a close collaboration between domain experts and product-minded engineers can produce meaningful, measurable results—turning sophisticated AI into real-world strategy.
