Electe's answer

Electe aims to create significant benefits for its customers by improving their experience in using its products and services. Data analysis tools and artificial intelligence-based solutions enable SMEs to make more informed, data-driven decisions. Companies expect a solution such as this to improve operational efficiency and reduce the time needed to perform manual and repetitive tasks, allowing them to focus on the core business. AI-based analytics tools and data integration capabilities can meet these expectations, helping companies make more informed decisions and more easily monitor the process of achieving their goals.

ChartGEX's answer:

Most options tools show you open interest and volume — and stop there. ChartGEX goes a layer deeper by quantifying what dealers are actually forced to do because of that positioning. That's the core difference.

When a market maker sells options, they have to delta-hedge continuously. That hedging isn't random — it creates mechanical buying and selling pressure at specific strikes. ChartGEX maps those obligations in real time, so you can see where price is likely to get pinned, repelled, or accelerated before it happens — not after.

Beyond GEX, the platform layers in Vanna and Charm flow analysis, which tell you how dealer hedging behavior shifts as volatility moves and time decays. That's what drives the 2pm melt-ups, the OpEx pins, the charm-driven drifts that catch most traders off guard. ChartGEX surfaces those dynamics explicitly.

Then there's the ML prediction layer — directional forecasts calibrated to specific strike-level mechanics, not generic trend signals. It synthesizes gamma positioning, flow imbalances, and vol regime data into something actionable: a structural lean that either aligns with your thesis or tells you to wait.

The data is sourced from institutional-grade feeds (OPRA-level), updated continuously throughout the session. That's not standard for retail-facing tools. Most platforms run on delayed snapshots. ChartGEX doesn't.

Electe's answer

Electe differs from competitors in its easy-to-use interface, customizable reporting options, and a market strategy targeted at small and medium-sized businesses. Electe's pricing model is also more affordable than its competitors, making it an attractive option for small businesses. In addition, Electe plans to offer a discount and referral program to incentivize current customers to refer new customers. The competitive landscape of the data analytics platform market has become increasingly crowded in recent years, with many new entrants and established players vying for market share. The market is dominated by large players, but there is also a growing demand for options that are easier and cheaper to use. As the market continues to evolve, it will be important to stay ahead of the competition by continuing to offer innovative features and a focused market strategy

ChartGEX's answer:

The alternatives — TradingView, FinViz, OptionCharts.io — are useful tools, but they're built around different assumptions about how markets work. They focus on price history, technical patterns, and static open interest. ChartGEX is built around market structure: specifically, what options dealers are obligated to do based on their current hedging positions.

That distinction matters in practice. GEX walls don't show up on a candlestick chart. The gamma flip level that determines whether dealers suppress or amplify the next move isn't something a moving average will tell you. ChartGEX gives you that structural context as a first-class input — not an afterthought.

A few specific reasons traders choose ChartGEX over the alternatives:

The GEX analysis is calculated from real institutional-grade data, not delayed retail feeds. That matters especially for 0DTE and intraday trading where stale data is worse than no data.

Vanna and Charm flows are included. Most competing tools don't touch these at all, even though they're central to understanding why price accelerates into OpEx or why vol expansion doesn't follow through.

The ML prediction layer adds a directional signal that's tied to structural positioning, not just historical price behavior. It's a pressure test on your thesis, not a replacement for it.

And at $29/month after a free trial, the price point is a fraction of what institutional analytics desks charge for similar data. For independent traders and small prop shops, ChartGEX is the only place this level of analysis is even accessible.

Electe's answer

The service proposed by Electe is aimed at SMEs at this stage. The target market does not consist of a well-defined type of company but includes all companies, which are daily in the condition of having to make managerial decisions with positive and negative repercussions that will affect the entire business reality. Electe, will mainly target small and medium-sized enterprises because they have structural and business organization characteristics for which they might be interested in receiving support through the use of software that reduces the commitment of internal resources. In addition, resorting to the use of an innovative digital platform increases the digitization process of companies, the main goal of the NRP. Especially considering that the digital transition is proceeding slowly in our country, new software using AI can increase its attractiveness to businesses. Electe's target companies are, specifically, all those businesses that perform important data analysis that can be complicated and time-consuming and resource-intensive for the individual company.

ChartGEX's answer:

ChartGEX is built for traders who already have a baseline understanding of options markets and want to go deeper into the mechanics of price movement. It's not a beginner platform — and it doesn't try to be.

The core audience breaks down into a few groups:

Active retail traders who trade SPX, SPY, QQQ, or individual equities with options exposure. They're typically running 0DTE or short-dated strategies and need real-time structural levels — gamma walls, flip points, magnet strikes — rather than lagging indicators.

Independent professionals and prop traders who manage meaningful position sizes and need data that holds up under pressure. For them, the cost of a bad read on market structure far exceeds a $29/month subscription.

Systematic traders who are building edge into their process. ChartGEX's API access makes it straightforward to pull GEX, Vanna, and Charm data directly into a trading model or alerting system.

What ties them all together is a frustration with tools that explain what happened after the fact. ChartGEX is specifically for traders who want to understand the structural forces shaping price before the move develops — not after it's already played out on the tape.

Electe's answer

Electe S.r.l. was born from the idea of Fabio Lauria who, in February 2023, decided to establish an innovative start-up to formalize his business and service, namely a platform for collecting a large amount of data that, through the use of modern I4.0 technologies such as artificial intelligence, is able to elaborate strategic management solutions for small and medium-sized enterprises. Electe is the result of the experience and resourcefulness of its founder, a manager who, despite his young age, has more than 10 years of professional experience in the field of technological systems and who, for 3 years, served as CEO at a company that provides plant solutions dedicated to the industrial, civil and tertiary sectors. It is precisely management's awareness and in-depth knowledge of the industry that is behind the idea that led to the establishment of Electe S.r.l., whose vision is to revolutionize data analysis through artificial intelligence, offering innovative solutions to improve business decisions and operational efficiency. Guided by the charismatic leadership of its founder, Electe aims to become a global benchmark in the industry.

ChartGEX's answer:

ChartGEX started from a pretty simple observation: the options market is the most information-rich market in the world, and most traders are using maybe 5% of what's actually in there.

The tools that existed were either too basic — open interest charts, put/call ratios — or locked behind institutional infrastructure that costs thousands of dollars a month. The analytics that serious options desks rely on, things like gamma exposure mapping, Vanna flow modeling, charm decay — those just weren't accessible to independent traders.

The goal was to change that. Not by dumbing the data down, but by building an interface that makes complex positioning data actually usable in a live trading session. You shouldn't need a quant background to know whether the current gamma regime favors fading moves or riding them. That answer should be visible in under a minute.

So ChartGEX was built with that constraint in mind: institutional-grade data, engineered for practical daily use. The ML layer came later, as a way to synthesize the positioning signals into something that pressure-tests your existing thesis rather than replacing your judgment entirely.

It's still early. The platform keeps evolving based on direct feedback from the traders using it. But the core belief hasn't changed — every trader deserves access to the same structural intelligence that institutions use to make decisions.

Electe's answer

Python, Machine Learning, Natural Language Processing, Cloud Infrastructure

ChartGEX's answer:

The frontend is built on Next.js, which gives us server-side rendering where it matters for performance and a clean component structure for the dashboard UI. The charting layer handles real-time data visualization across multiple instruments and expiration cycles simultaneously, so responsiveness under load was a key design constraint from the start.

On the data side, the platform ingests options chain data from institutional-grade feeds — open interest, volume, implied volatility surfaces, and Greeks across every listed strike. The GEX, Vanna, and Charm calculations run continuously throughout the session, which requires a backend infrastructure that can process and serve that data with minimal latency.

The ML prediction layer is a separate model pipeline trained on gamma positioning, options flow, and volatility regime data. It's designed to output calibrated directional forecasts rather than binary signals — which means the model architecture prioritizes reliability over novelty.

The API is built to be developer-friendly for systematic traders who want to pull positioning data directly into their own workflows or alerting systems.

Electe's answer

• Retail and e-commerce companies optimizing sales and inventory decisions
• Manufacturing firms using predictive analytics for operations
• Healthcare organizations streamlining data-driven workflows
• Financial services companies automating reporting and compliance
• Professional services firms leveraging AI for client insights