✦ New AI-powered root cause analysis for enterprise teams

Debug Any Issue.
Understand Every Flow.

NxtOne captures runtime execution as semantic knowledge graphs, giving your team instant root cause analysis and deep system understanding — without debugging a single line of code.

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NxtOne — OrderService Investigation
NxtOne AI Investigator
Why are premium customers being charged standard shipping on orders over £100?
I've traced the order flow through 1,247 events across 4 services.

Root cause: PricingService.applyDiscount() evaluates shipping rules before LoyaltyService.resolveCustomerTier() returns. The async call was reordered during the Feb 3 refactor — so every customer evaluates as tier: null, defaulting to standard rates.
How many customers were affected?
3,847 orders since Feb 3. The execution path:
OrderService → PricingService → LoyaltyService

The fix: move the await on resolveCustomerTier() before applyDiscount() in CheckoutOrchestrator.java:89
Ask about this investigation...
Designed for teams building at scale
Spring BootPythonNode.jsAWSAzureKubernetesKafka
The Problem
Debugging distributed systems
is still broken.

Your team wastes hours per incident digging through logs, traces, and metrics — piecing together what happened across dozens of services.

🔍

Hours lost per incident

Engineers spend more time searching logs than actually fixing issues. Context is spread across 10+ tools with no unified view.

🧩

No one sees the full picture

New team members take months to understand how the system actually behaves. Tribal knowledge lives in people’s heads.

Same bugs, different day

Without understanding root causes, teams fix symptoms instead of underlying issues. The same patterns keep recurring.

$grep -r "NullPointerException" /var/log/
... 2,847 results found
$kubectl logs order-service-7d4f8 --tail=500
ERROR [2025-01-15 14:32:07] NullPointerException
at InventoryService.checkStock(StockValidator.java:142)
at OrderProcessor.processOrder(OrderProcessor.java:89)
at PaymentGateway.handleCallback(Gateway.java:203)
WARN Which service caused this? 🤔
// 3 hours later, you're still searching...
$open datadog.com/apm/traces/...
$open kibana.internal/discover/...
$open grafana.internal/explore/...
// Still no clear answer. 😓
How It Works
From chaos to clarity
in three steps.

NxtOne captures what your system actually does at runtime and makes it understandable — to humans and AI.

1

Capture

Connect your repo and NxtOne analyses your entire codebase — method calls, data transformations, service interactions — building a complete picture of how your system actually behaves.

// Connect your repo, NxtOne does the rest

$ nxtone upload ./my-project

✓ Scanning source code...
✓ Mapping 847 methods across 6 services
✓ Building execution graph...
✓ Ready — ask anything
2

Map

Captured events are transformed into a semantic ontology graph — a knowledge structure that represents how your system actually behaves, stored in Graph Database for instant querying.

(Order)──CALLS──▶(Payment)
  │
  ├──WRITES──▶(OrderDB)
  │
  └──EMITS──▶(NotifyQueue)

// 847 events → 1 clear graph
3

Reason

Ask NxtOne anything. Our AI reasons over the knowledge graph to instantly identify root causes, explain behavior, and suggest fixes — in plain English.

"Why is checkout failing?"

→ Tracing 6 services...
→ Root cause identified
→ Fix: StockValidator.java:142

// 30 seconds. Not 3 hours.
Capabilities
Everything you need to
understand your system.

NxtOne isn't another monitoring tool. It's operational intelligence — giving every team member a deep understanding of how your software actually works.

🧠

AI Root Cause Analysis

Ask "why did this fail?" and get an instant, accurate answer. NxtOne’s AI reasons over your system’s actual execution graph — not just logs — to pinpoint exact root causes across service boundaries.

▶ Investigation #2847

Q: Why did Order #38291 fail?

Root Cause Analysis:
The order failed because
InventoryService.checkStock()
received a null warehouse_region
for EU orders after the Jan 15
database migration.

Suggested Fix →
Add null check at line 142
📊

Semantic Knowledge Graphs

See your system as a living, queryable graph of relationships — services, methods, data flows, and dependencies — all captured from actual runtime behavior.

Execution Time Machine

Replay any execution flow step-by-step. Scrub through time to see exactly what happened, when, and in what order — like a DVR for your distributed system.

🚀

Instant Onboarding

New team members can ask NxtOne "how does the checkout flow work?" and get an accurate answer from the actual system behavior — not outdated documentation.

🔗

Cross-Service Tracing

Follow any request across every microservice it touches. NxtOne automatically maps the full distributed execution path with zero manual instrumentation.

Why NxtOne
Not another monitoring tool.

Traditional tools show you what happened. NxtOne tells you why — and how to fix it.

CapabilityLog AggregatorsAPM ToolsLLM ProvidersNxtOne
Root cause identificationManual searchPartial tracesStatic guesses✓ AI + runtime graph
System understandingNoneService maps onlyCode-level only✓ Full semantic graph
Code-level visibilityLog lines onlyMethod-level spansStatic analysis✓ Execution + data flow
Natural language queries✓ Chat-based✓ Ask anything
Runtime contextMetrics & traces✗ No runtime data✓ Full execution capture
Business logic bugs✗ Only crashes✗ Guesses from code✓ Detects wrong outcomes
Team onboardingPartial✓ Instant system knowledge
Time to root causeHours30–60 minutesMinutes (if lucky)✓ Under 60 seconds
FAQ
Frequently asked questions.
Traditional APM tools detect failures — crashes, exceptions, timeouts. But when the app runs perfectly and returns 200 OK, yet a customer is charged twice or an order ships to the wrong warehouse, those tools see nothing wrong. NxtOne captures the full execution semantics, so AI can reason about business logic correctness — not just technical health. It's the difference between "Did the code crash?" and "Did the code do the right thing?"
NxtOne uses lightweight agents that attach to your runtime (JVM, Python, Node.js). They capture method calls, data flows, and service interactions with minimal overhead — typically less than 3% CPU impact. No code changes required beyond adding the agent.
We currently support Java/Spring Boot, Python, and Node.js with more languages coming soon. Our agents work with any framework built on these runtimes — Spring, Django, FastAPI, Express, NestJS, and more.
NxtOne's agent captures source code, execution data, and runtime variables to power full AI reasoning — but everything is encrypted end-to-end. No one at NxtOne can view your code, data, or variables. All data is encrypted in transit (TLS 1.3) and at rest (AES-256). We offer both cloud-hosted and on-premise deployment options for enterprise customers.
Most teams are up and running in under 30 minutes. Add our agent to your application, deploy, and NxtOne begins capturing execution data immediately. You’ll see your first knowledge graph within minutes of your first request.
Stop guessing.
Start understanding.

Join the engineering teams using NxtOne to debug faster, onboard quicker, and build with confidence.