From Black Box to Full Transparency
Arize AX shows your teams what is happening inside an LLM app and how it will perform for real users.
Why QKTech and Arize?
AI applications often behave one way in testing and another in production. Agents loop or fail without warning, and compliance teams lack clear visibility.
Arize AX shows technical teams and domain experts what is happening inside an LLM app and how well it will work for real users. It then recommends changes. It combines tracing, evaluation, experiments and monitoring in one engineering platform for building more advanced LLM applications and agents.
QKTech puts Arize to work with deep experience in quality engineering and AI reliability. We use Phoenix, Arize’s open-source observability toolkit and OpenTelemetry to instrument LLM applications and agents. We route production data into Arize AX and define clear evaluation and incident processes.
Enterprises get a single view of prompts, agents, tools and models, with full setup, governance and ongoing operations support. The same foundation works across assistants, RAG-based applications, multi-step agents and AI-powered workflows in banking, financial services, insurance, tech and digital natives, capital markets, retail and automotive.
Success metrics
Scales to
more than one trillion inferences and spans each month
Tens of
millions
Of evaluation runs logged monthly to support continuous improvement
Complete
AI agent traces across development and production for faster debugging
Clear
Audit trails for prompts, responses and decisions to support compliance
Less
Manual evaluation effort through reusable templates and sampling
Value adds and business results
The capabilities below are the ones teams rely on most in day-to-day use.
Unified LLM and Agent Tracing with AX and Phoenix
Guardrails, Monitoring and AI Quality SLAs
Evaluation at Scale for Real Business Tasks
Datasets, Experiments and Continuous Improvement
Unified LLM and Agent Tracing with AX and Phoenix
Arize AX and Phoenix capture detailed traces of every AI interaction, from user input through tools and external services to the final response. Teams can search for slow, costly or low-quality interactions and drill into each step. Technical users get span and trace views. Non-technical users can review conversations and high-level analytics. QKTech designs the tracing strategy, configures Phoenix and OpenTelemetry, connects traces to Arize AX and maps them to journeys and KPIs for product, data and SRE teams. We also advise on context propagation across services, applications and agents.
Guardrails, Monitoring and AI Quality SLAs
Arize AX turns traces and evaluations into live monitoring. Teams track hallucination patterns, PII or policy violations, latency, cost, quality and performance in one place, with alerts when thresholds are breached. Online evaluations score behavior automatically. QKTech defines SLAs and SLOs for key AI journeys, configures monitors and alerts and integrates them with your incident and service management tools. We set up guardrails and workflows for quick triage and connect AI quality signals to your existing observability stack.
Evaluation at Scale for Real Business Tasks
Arize AX and Phoenix provide evaluation libraries, templates and LLM-as-a-judge support. Teams score answers, summaries, classifications and tool use against domain and policy criteria. Signals come from LLM-as-a-judge, curated golden datasets, user feedback or code-based checks. QKTech defines an evaluation strategy per use case, builds custom evaluators, sets up scoring pipelines and embeds evaluation into CI/CD and release gates. We help choose metrics for each pattern: relevance and hallucination for RAG, resolution and empathy for support agents and accuracy and policy fit for lending or risk workflows.
Datasets, Experiments and Continuous Improvement
Arize supports curated datasets, experiments and analytics to compare prompts, models, retrieval strategies and agent flows over time. Datasets can be built from live traces or uploaded CSVs. QKTech builds golden datasets, configures experiments and runs structured tests to improve accuracy, safety and cost. We review observability insights and recommend prompt, policy and data changes. We also help non-technical stakeholders use Arize’s prompt playground alongside engineering teams.
Leading thoughts
Insights
Common questions about Arize and QKTech
What is Arize AX?
Arize AX is an AI observability and evaluation platform. It combines tracing, evaluation, experiments and monitoring for LLM applications and agents.
What is Arize Phoenix?
Phoenix is Arize’s open-source observability toolkit. QKTech uses it with OpenTelemetry to instrument LLM applications and agents and route production data into Arize AX.
How does QKTech help with LLM observability?
QKTech designs the tracing strategy, sets up monitors and evaluations and defines incident processes. We also run the platform and improve it over time.
Can Arize monitor AI agents in production?
Yes. Arize AX captures traces of every agent step and monitors hallucination, policy violations, latency and cost. It alerts teams when thresholds are breached.
Get insights that matter. Deliver experiences that are simply better.
Schedule a consultation or request an Arize AX demo with our experts.