AI ThinkPanel

Ask Your Data. Get Answers. Instantly.

Talk to your data and unlock intelligence around you

AI ThinkPanel is an AI-powered natural-language analytics solution that enables anyone to query data, run calculations, and access contextual insights instantly — without SQL or technical support. By removing reporting bottlenecks, it accelerates decision-making and empowers teams to act faster and resolve issues proactively.

LLM-independent and deployable on-prem or in any cloud, ThinkPanel combines customizable intelligence, strong governance, secure audit trails, and self-service analytics in one interface. With immediate data availability and tailored insights, it drives smarter decisions and measurable business outcomes across the enterprise.

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Benefits

Talk to your data

Ask questions in natural language - in any language - and receive instant answers. No SQL, no specialized skills, just direct access to insights.

True Self-Service Intelligence

Empowers every team to access and analyze data instantly, streamlining reporting workflows and accelerating decision-making.

Built-In Governance 
& Trust

Every interaction is securely logged, enabling auditability, traceability, and safe knowledge reuse across your organization.

Intelligence built around you

Customize the agent to reflect your business logic, models, and KPIs, delivering contextual insights that adapt to each team’s needs.

Challenges

Limited Access to Data Insights

Limited Access to Data Insights

Teams without technical or SQL expertise struggle to independently query data, creating delays and limiting visibility.

Slow, Fragmented Reporting

Slow, Fragmented Reporting

Manual data retrieval and dispersed analytics tools lead to reporting queues, slowing decisions and reducing organizational agility.

Increased Security & Compliance Exposure

Increased Security & Compliance Exposure

Uncontrolled data access and ad-hoc data sharing heighten security risks and make compliance and auditing more complex.

Inconsistent Visibility Across Systems

Inconsistent Visibility Across Systems

Siloed systems, dashboards, and logs create blind spots, making it difficult for teams to quickly identify issues and uncover actionable insights.
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Use Case | Telco

A major telecommunications provider operating complex network infrastructure, requiring efficient and accurate monitoring to ensure service continuity and operational excellence.

The challenge:

With a growing network, outdated and unused monitoring rules created excessive noise and slowed incident response. Limited visibility into linked documentation further delayed troubleshooting. The goal was to simplify monitoring logic, cut operational overhead, and help teams focus on critical issues.

Our approach:

Natural Language Access
Implemented OpsAgent to allow operations teams to query monitoring data in natural language, reducing dependency on technical scripts.
Automated Rule Analysis
Integrated automated detection of outdated and unused monitoring rules to streamline cleanup and maintain accuracy.
Linked Documentation Retrieval
Enabled instant access to related documentation,
empowering faster decision-making and incident resolution.

The results:

Reduced Monitoring Noise
 
Significant drop in false positives, improving focus on real incidents.
Faster Incident Resolution

Natural language queries and linked documentation accelerated troubleshooting and response times.

Optimized Monitoring Environment

Continuous cleanup of unused rules maintained a lean, efficient, and accurate monitoring framework.

Use Case | Telco

Operating one of the most extensive telecom networks in the region, the provider needed smarter ways to manage thousands of daily alarms and maintain high service availability.

The challenge:

With massive volumes of Netcool alarms, the operations team struggled to detect recurring issues and filter noise. The flood of alerts complicated prioritization, slowed resolution, and increased operational strain. The goal was to uncover patterns, cut redundant alarms, and enable faster response to critical events.

Our approach:

Natural Language Queries
Enabled teams to analyze Netcool alarms using OpsAgent through simple, natural language questions.
Alarm Frequency Analysis
Delivered insights into recurring alerts per application to pinpoint noise sources and underlying issues.
Data-Driven Prioritization
Provided actionable intelligence to focus efforts on the most impactful incidents.

The results:

Clearer Alarm Landscape
 
Highlighted recurring alerts and removed redundant rules, creating a cleaner, more actionable alarm system
Proactive Issue Management

Early detection of repetitive alarms helped teams address root causes before they escalated.

Lower Operational Load
Reduced manual filtering of alerts, freeing up resources to focus on
critical network events.

Use Case | Energy

With a portfolio of large-scale solar parks, this energy provider needed a smarter way to monitor asset performance and ensure optimal energy output across distributed sites.

The challenge:

Managing multiple inverters across several solar parks made it difficult to quickly detect performance drops and underutilized assets. Manual data collection and reporting slowed diagnostics and delayed maintenance actions. The goal was to gain real-time visibility, accelerate troubleshooting, and maximize overall energy production.

Our approach:

OpsAgent  Integration
Connected asset data from all solar parks into a centralized, queryable interface.
Performance Benchmarking
Enabled natural language comparisons of inverter output to detect underperforming units instantly.
Automated Reporting
Generated real-time reports to support faster diagnostics and maintenance prioritization.

The results:

Improved Energy Yield
 
Early detection of inefficiencies increased overall solar production
output.
Faster Diagnostics

Real-time performance insights reduced the time to identify and fix
underperforming assets.

Streamlined Operations
Automated reporting minimized manual work, enabling teams to
focus on optimization and maintenance planning.

Use Case | Energy

Managing a diverse network of oil wells across multiple sites, the company needed a more efficient way to track production trends and ensure consistent operational performance.

The challenge:

Production and downtime data were siloed across different wells, making it hard to spot anomalies or benchmark performance. Manual analysis delayed maintenance decisions, increasing the risk of extended downtime and reduced output. The goal was to centralize data access, accelerate anomaly detection, and prioritize interventions to maintain optimal production levels.

Our approach:

Unified Data Access
Integrated production and downtime metrics into OpsAgent for on-demand comparison across wells.
Anomaly Detection
Enabled teams to quickly identify deviations in performance and address potential issues before escalation.
Performance Benchmarking
Provided insights to rank wells by output and guide maintenance priorities effectively.

The results:

Optimized Production Efficiency
 
Faster detection of performance gaps improved overall oil yield.
Reduced Downtime Impact

Prioritized maintenance actions minimized disruptions and sustained output levels.

Data-Driven Decision-Making
Centralized insights empowered operations teams to act proactively and plan interventions with greater accuracy.

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© 2025 InnoWave. All rights reserved

Privacy Policy

Contacts

PT: +351 213 174 421
UK: +44 203 771 7300
US: +1 571-314-0931
BE: +32 2 203 87 41
IN: +91 88843 34234

Contact Us

Sponsored

© 2025 InnoWave. All rights reserved

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