Your Agentic Stack is Leaking Money and Performance. We Pinpoint the Leaks.
Stop guessing. Harmonize the cost, latency, quality, and throughput of your AI operations in a single control plane. Netra Apex is the AIOps co-optimization agent for high-performance AI.
Request a Pilot & See Your Savings ReportFrom Chaotic Liability to Clear Assets
The Complexity Trap
In the race to innovate, engineering teams are navigating a labyrinth of complex technical trade-offs that span the entire inference stack. For high-usage agentic systems, the challenge is not a lack of options, but a paralyzing complexity of choice. This environment forces teams into a cycle of reactive, chaotic one-offs instead of continuous, strategic optimization, turning a key competitive advantage into a source of operational drag.
The Hidden Costs of Your "AI Factory"
Rough, aggregate dashboards and a growing list of per-token costs don't reveal the underlying inefficiencies driving up your spend and slowing down your system. Teams are left fighting constant bill surprises and dedicating valuable engineering cycles to ad-hoc analysis and intuition-based guesswork, pulling them away from building core product features. The result is a system that is more expensive, slower, and less reliable than it should be.
The Chaotic Era of AI Ops
An AI-Native Control Plane for AIOps
Netra Apex is the co-pilot for your engineering team. We work with your existing stack to transform volatile trade-offs into a managed, competitive advantage.
Profile Every AI-Native Workload
Transforms each request into a rich Workload Profile, capturing semantic intent, risk profile, and required SLOs (TTFT/TPOT), while detecting issues like context rot across multi-turn interactions.
Map Your AI Supplies
Maintains a live Supply Catalog of your entire AI supply chain (APIs, self-hosted), detailing specs like quantization, architecture, and tokenizer profiles.
Find the Pareto-Optimal Front
For each Workload Profile, we identify the Pareto-optimal set of supply options, showing you the most efficient trade-offs between cost, latency, and quality so you can choose the right option for that specific job.
Close the Loop
Our Observability Plane feeds empirical, post-execution data back into the Supply Catalog, ensuring your decisions are always based on the latest performance and quality metrics.
Actionable Intelligence for the Entire AI Stack
Netra Apex provides system-level visibility whether you're building on third-party APIs or self-hosting models. We surface the "unknown unknowns" and provide the data to make confident, high-impact optimization decisions.
- Action Optimizations Fast Proactively tune your AI system for the best possible user experience, moving beyond reactive fixes to data-driven enhancements.
- Scale Unit Economics Get accurate performance profiles and costs for meaningful units of work in an AI-first world to achieve predictable COGS.
- Demystify AI Behavior Go beyond infrastructure metrics. Understand the performance and cost implications of every agentic step, tool call, and user interaction.
- Works With Your Agentic Frameworks Whether you're building with LangChain, LlamaIndex, or custom agentic architectures, Netra Apex provides the underlying visibility to optimize tool-use, routing, and planning steps where tokens are consumed. Learn more
Turn Your API Spend into a Strategic Advantage
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Pinpoint API & Model Inefficiencies
Go beyond top-level cost aggregation. Netra Apex analyzes request patterns to flag costly
max_tokenssettings, identify workloads perfect for cost-saving features like OpenAI's 50% discount Batch API, and surface verbose conversational filler in prompts that inflates every single call. - Quantify the ROI of Advanced Caching Stop guessing if a semantic cache is worth the engineering effort. Netra Apex analyzes your query streams to model the potential hit rate and cost savings of moving beyond exact-match, giving you a data-driven case for building a vector-based caching solution.
- Execute Data-Driven Model Selection Move beyond public leaderboards that don't reflect your reality. Netra Apex systematically evaluates different models against your unique, auto-discovered traffic patterns to find the optimal price-performance point for each specific task in your agentic system. Find the Pareto-optimal front for every task.
Unlock the Full Potential of Your Silicon
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Master Scheduler & Cache Trade-Offs
Generic benchmarks lead to sub-optimal user experiences. We provide deep visibility into the critical trade-off between Time-to-First-Token (
TTFT) and Inter-Token-Latency (ITL), helping you tune your scheduler for chat vs. summarization. Diagnose KV Cache memory fragmentation and quantify the performance impact of strategies like PagedAttention. - De-Risk Advanced Optimization Strategies Implement cutting-edge techniques with confidence. Netra Apex guides your speculative decoding efforts by recommending optimal low-latency draft models, preventing misguided efforts. It also quantifies the potential 2-4x performance gain from hardware-specific compilers like TensorRT-LLM, providing a clear cost-benefit analysis before you commit resources.
- Surface Fleet-Wide Redundancies Stop wasting cycles on redundant computation. Our system analyzes traffic across your entire fleet to identify massive cross-request opportunities, like quantifying the performance gain of implementing a shared Prefix Cache for a common system prompt—an optimization invisible at the single-instance level.
The Netra Apex Advantage: A Unified View
The path to high-performance AI requires navigating complex choices. The standard approach is manual, slow, and relies on incomplete data. Netra Apex provides the system-level visibility to make informed, data-driven decisions.
| Optimization Challenge | Applies To | Standard Manual Approach | The Netra Apex Co-Agent |
|---|---|---|---|
| API Cost/Latency | All | Manual review of high-level dashboards, bills, and code; ad-hoc analysis of prompts and API parameters. | Identifies Inefficiencies: Flags costly parameter settings (max_tokens), highlights opportunities for batching, and pinpoints verbose prompts to target for optimization. |
| Model Selection | All | Running ad-hoc limited evaluations; relying on public leaderboards that may not reflect real-world performance on specific tasks. | Data-Driven Selection: Systematically evaluates multiple models against ultra-specific auto-discovered traffic patterns to find the optimal price/performance point for each task. |
| Fine-Tuning vs. Prompting | All | Intuition-based decision; costly trial-and-error experiments with fine-tuning without clear ROI estimates. | Models ROI of Fine-Tuning: Analyzes prompt patterns and identifies tasks where fine-tuning a smaller model could yield similar quality at a fraction of the cost. |
| Scheduler Tuning (TTFT vs. ITL) | Self-Hosted | Set a static scheduler configuration based on generic benchmarks, leading to a sub-optimal latency profile for mixed workloads. | Provides Latency Visibility: Analyzes workloads and models the impact of scheduler settings on user-facing metrics (TTFT vs. ITL), enabling task-specific tuning. |
| Speculative Decoding | Self-Hosted | A complex, manual R&D process with a high risk of mis-optimizing for draft model accuracy instead of latency. | Guides Implementation: Recommends suitable, low-latency draft models and provides analysis that steers teams toward proven, latency-focused optimization strategies. |
| Hardware-Specific Compilation | Self-Hosted | Often skipped due to high operational complexity, leaving a 2-4x performance gain on the table. | Quantifies Opportunity: Analyzes the model/hardware pair and estimates the potential performance gain from compilation, providing a clear cost-benefit analysis. |
| Multi-Request Efficiency | All | Default to stateless scaling, leading to massive computational redundancy as common prompts are re-processed for every request. | Surfaces Redundancy: Analyzes fleet-wide traffic to identify and quantify the potential gains from cross-request strategies like Prefix Caching. |
Enterprise-Grade Security & Fast Setup
We proactively address the two biggest barriers to starting a pilot: data security and implementation complexity. Get started with confidence.
A Security Model Built for High-Stakes Environments
Your data remains your data. We never need access to your raw, sensitive information. Netra Apex is designed from the ground up to operate on sanitized logs, ensuring you maintain full control and compliance. Our system connects via a dedicated, read-only ClickHouse user that you create and control. We provide robust, documented methods for PII redaction before any data is ever ingested by our platform.
Granular Data Control
Choose the level of redaction that meets your compliance needs, from targeted PII removal to total object redaction. Our sophisticated understanding of data privacy gives you complete control.
Read the Full Data Security & Redaction Guide →Go Live in Days, Not Months
Getting started is straightforward and designed to minimize engineering overhead. The process is a simple, secure ClickHouse-to-ClickHouse connection. There are no complex agents to install or sidecars to manage, eliminating a common point of failure and maintenance.
- Create a Secure User: Set up a dedicated, read-only user in your ClickHouse database for Netra.
- Clean Your Data: Choose a cleaning method. We provide a native SQL Materialized View for a quick setup, or a high-accuracy Python script using Microsoft's Presidio library for comprehensive PII redaction.
- Grant Access: Point Netra to the sanitized table.
That's it. Your LLM logs create a continuous, secure pipeline for analysis, allowing you to see value almost immediately.
View the 3-Step ClickHouse Integration Guide →Your Path from Chaos to Control Starts Here
Get Your Personalized Savings Report
Start a pilot and connect your data to see exactly how Netra Apex can identify and unlock significant savings by optimizing API calls, model selection, and caching strategies for your specific workloads.
Request a PilotExplore the Live Demo
Interact with a live demo environment. See dynamic supply and demand balancing in action and explore how the platform surfaces actionable insights from raw log data.
Explore Live DemoTransform AI Operations into a Co-Optimized Engine for Growth.
Stop the manual fire-fighting. Move from chaotic one-offs to continuous, strategic optimization that drives your competitive advantage. The ultimate benefit is unlocking your most valuable resource—your engineering talent—to focus on building the product features that create defensible market value.
Request Your Pilot