Predict Trends. Detect Anomalies. Prevent Disruptions.

Harness AI-powered time series and anomaly detection to identify patterns, forecast future events, and catch irregularities before they cause costly problems.

Overview

GullyAI's Time Series Analysis & Anomaly Detection solutions transform raw, time-stamped data into clear forecasts and alerts. Using advanced statistical models, deep learning architectures, and domain-specific tuning, we help businesses detect irregularities, predict demand, and mitigate risks in real time. Whether it's financial fraud prevention, IoT sensor monitoring, energy consumption optimisation, cybersecurity breach detection, or supply chain disruption alerts, our solutions deliver the insight and speed required to stay ahead.

Benefits

Early Issue Detection

Identify anomalies as they occur to prevent fraud, equipment failure, cyberattacks, or service outages before they escalate into major incidents

Accurate Trend Forecasting

Use historical and live data to anticipate demand, detect seasonality, and plan resources with high confidence across multiple time horizons

Reduced Downtime & Losses

Act on real-time alerts to minimise production downtime, inventory shortages, or unexpected operational costs

Improved Risk Management

Spot irregularities that signal compliance violations, safety hazards, or security threats, enabling proactive resolution

Scalable Across Systems

Monitor and analyse high-volume, multi-source time series data across distributed assets, locations, or business units

Features

Advanced Forecasting Models

Leverage ARIMA, Prophet, LSTM, and hybrid models to predict trends, seasonal patterns, and cyclical behavior accurately

Real-Time Anomaly Detection

Apply streaming analytics to identify sudden deviations, unexpected spikes, or drops in key metrics as they happen

Multi-Granularity Analysis

Support second-level, minute-level, or monthly data granularity, making it suitable for both high-frequency trading and long-term planning

Root Cause Analysis

Correlate anomalies with related metrics and events to understand the underlying causes and take targeted corrective action

Integration with Existing Tools

Connect seamlessly with BI dashboards, monitoring systems, and IoT platforms for centralised insights

Automated Alerts & Reports

Configure threshold-based and AI-driven notifications via email, SMS, or API to ensure fast incident response

Use Cases

Finance

Detect suspicious transaction spikes, forecast cash flows, and monitor trading activity for anomalies that may indicate fraud or market instability

IoT Monitoring

Track sensor data from connected devices to detect malfunctions, unusual activity, or environmental threshold breaches in real time

Energy Management

Forecast energy demand, detect equipment inefficiencies, and identify abnormal consumption patterns for cost savings and reliability

Cybersecurity

Spot unusual network traffic, login patterns, or system behaviors that may indicate intrusions or malware activity

Supply Chain

Monitor shipment data, inventory levels, and lead times to detect potential delays, demand surges, or logistic bottlenecks

Our Process

Requirement Analysis

Understand your data sources, goals, and anomaly tolerance thresholds to define the project scope

Data Preparation

Clean, normalise, and align time-series data from multiple systems to ensure model readiness

Model Selection & Training

Choose and train models suited for your data volume, velocity, and seasonality patterns

Validation & Benchmarking

Test model accuracy and alert precision against historical incidents and baseline performance

Deployment

Integrate the solution into your operational systems for live monitoring and alerting

Continuous Improvement

Monitor performance, retrain models, and fine-tune detection parameters as conditions evolve.

Why Choose Us

Domain Expertise

Experience in finance, IoT, energy, cybersecurity, and supply chain ensures solutions are customised to industry-specific needs

High Accuracy Models

Use of advanced algorithms and ensemble techniques improves both forecast reliability and anomaly detection rates

Real-Time Capabilities

Support for streaming data ensures anomalies are flagged instantly, enabling rapid response

Customisable Alerts

Configure detection sensitivity and reporting to match operational priorities and compliance requirements

Scalable Infrastructure

Capable of handling large-scale, high-frequency time series data without performance degradation

Frequently Asked Questions

Accuracy depends on data quality and volume, but our solutions consistently outperform traditional methods in precision and recall.

Yes, we provide APIs, connectors, and custom integration options for most BI, IoT, and security platforms.

Absolutely, we adjust model selection to perform effectively with both limited and large-scale datasets.

In real-time setups, anomalies can be flagged in seconds, enabling near-instant action.

We apply encryption, access control, and compliance measures aligned to your industry standards.

Anticipate. Detect. Respond.

Book a free consultation with GullyAI to explore how Time Series Analysis & Anomaly Detection can keep your operations predictable, secure, and efficient.

Book a Free Consultation