DigiEdze AI · Managed AI
Transform with AI for Accelerated Impact
Models change, data drifts, costs vary, and agents encounter unexpected behaviours that are never anticipated. This is where we operate the whole estate through monitoring, evaluating, securing, maintaining economics, and improving continuously being accountable.
- 24×7 AI monitoring
- model operations
- AgentOps
- AI incident management
- performance optimization
- AI FinOps
- security operations
- continuous improvement
Reference architecture
- 06Your AI estate
- 05Monitoring & evaluation plane
- 04AI on-call & incident process
- 03Model, prompt & agent operations
- 02FinOps optimization loop
- 01Service reporting & improvement plan
What Changes When This Goes Wrong?
The system was delivered and now quietly degrades because nobody owns it.
There is no AI on-call, so an AI incident becomes an unassigned escalation.
Improvement stops at go-live, which is precisely when the real learning starts.
What We Build
Our AI Managed Services
24×7 AI monitoring
Quality, latency, cost, safety and agent health watched continuously against defined service levels.
AI incident management
Defined severities, response paths and on-call for AI-specific failure modes, integrated with your existing process.
Model and prompt operations
Version management, provider changes, deprecations and regression testing handled as routine operations.
AgentOps-as-a-Service
Agent fleets monitored, evaluated, policy-tuned and cost-managed on your behalf.
Continuous AI FinOps
Ongoing routing, caching and capacity optimization with reporting against unit-cost targets.
Continuous improvement
Production failures fed back into datasets and evaluations, with a regular improvement cadence and reported outcomes.
How it works
Our AI-powered solutions assist enterprises with continuous monitoring and threat detection, navigating through challenging environments.
Technology
- dZops
- dZtrace
- dZopti
- dZshield
- Evaluation platforms
- Service management integration
Use Cases
Tailored to Modernize Industries
BFSI
Regulated AI estate operated with evidenced controls and monthly governance reporting.
Manufacturing
Agent fleets across plants operated centrally under one service level.
Technology
AI platform operations outsourced so internal engineers build rather than maintain.
Outcomes
What We Measure
Streamline operations and accelerate decision-making through optimal and scalable solutions, proven by in-depth expertise where we lead the technology alliances of the future.
- AI service availability
- Agent success rate over time
- Cost per task trend
- Improvement cycle cadence
Questions
Managed AI, Answered Directly
What does a Managed AI service level actually cover?
Availability of the AI services, response times by incident severity, evaluation cadence and quality thresholds, cost-per-task targets, security monitoring, and a defined improvement cycle with reported outcomes. Quality and unit cost are committed alongside uptime, because uptime alone does not describe whether AI is working.
Can you operate AI you did not build?
Yes. We start with an assessment of the current estate — architecture, evaluation coverage, observability, security posture and cost model — then close the gaps needed to operate it accountably before taking on the service.
Choose your starting point
Where Are You Today?
Enterprise AI conversations stall when the entry point is wrong. Pick the sentence that matches your situation.
We have an idea.
→ AI STRATEGY
We have a POC.
→ AI PRODUCTIONIZATION
We have an AI application.
→ LLMOPS / AGENTOPS
We need autonomous workflows.
→ AGENTIC AI
Our AI is too expensive.
→ AI FINOPS
Our AI can't reach enterprise knowledge.
→ RAG & KNOWLEDGE
We can't send data to public AI.
→ SOVEREIGN AI
We need to run AI securely.
→ AI SECURITY
Talk About Managed AI
From implementation of right AI solutions to continuous monitoring, we keep the promise of aligning the transformative core we are designing for you.
30 MINUTES WITH AN ARCHITECT · BRING YOUR HARDEST CONSTRAINT