Agentic AI

Modernization doesn’t need to be expensive - or disruptive. Torry Harris’ Agentic Modernization-as-a-Service (A-MaaS) uses autonomous AI agents to deconstruct, re-architect, and re-platform your legacy systems - at a fraction of the time and cost.

Agentic Modernization Journey:

• Decompose & document: Agents extract logic, map interdependencies, summarize legacy routines
• Blueprint the target: AI designs phased, cloud-native architectures using real-world telemetry
• Migrate & validate: Agents auto-map data schemas, simulate workloads, and ETL with built-in validation
• Test & optimize: AI generates regression tests and compares legacy vs modern system behavior
• Self-improve: Agents monitor and auto-remediate performance issues post go-live

Accelerators:

• TuringBots: Automate code summaries, re-architecture, ETL, and testing
• AI Factory: Low-cost teams implementing central agent orchestration and knowledge base
• 4Sight: Observability and performance monitoring

Outcome: 50% shorter modernization timelines - 18-month modernization down to 9 months, 30–40% Opex reduction, Zero business disruption via progressive cutover strategy, Explainable AI for risk-aware migration

From requirements to deployment, we - streamline delivery by embedding TuringBots - our proven frameworks like SDLC.ai and Ops.ai are deployed across the development lifecycle with zero drift. These modular agents work autonomously or alongside developers - to shift-left planning, automate code generation, enforce governance, and execute intelligent testing and release orchestration.

Why Traditional SDLC Needs Reinvention

• 30-40% higher design costs due to poor discoverability of software artifacts
• 50% higher dev costs due to lack of automation in code creation and documentation
• 60% slower MTTR due to fragmented ITSM handoffs
• 6000+ redundant DataOps pipelines in typical enterprises driving up costs

Agentic Delivery Flow:

• Parse specs → Auto-generate stories, test plans
• Generate code → Human-in-the-loop review
• Auto-integrate into CI/CD → Deploy & monitor
• Feedback loop → Refine agents using telemetry

Bonus: TuringBots are domain-trained (e.g., telco, banking) and reusable across pipelines.

Outcome: 3× velocity, 50% lower design and documentation effort, 40% increase in developer productivity, 60% higher release confidence, 70% automation coverage across dev and QA

Traditional enterprise testing is too slow, too manual, and too disconnected from development workflows. Torry Harris’ TuringQA brings Agentic AI into the testing lifecycle - enabling real-time test generation, intelligent regression, continuous feedback loops, and domain-trained QA agents that scale with your business.

TuringQA Components:

• Test plan generation
• User scenario modeling
• Coverage tracking across environments
• Auto-validation of test cases
• Defect logging and auto-remediation

Why Choose TuringQA?

Outcome: 70% faster regressions, 40% less QA effort, 50% fewer escaped defects, 100% traceability, Self-learning agents that improve cycle-over-cycle

Modern IT Ops teams are often overwhelmed by fragmented telemetry and mounting SLAs. Torry Harris brings Agentic AI into IT operations through autonomous agents that monitor systems, identify root causes, and remediate issues – with or without human-in-the-loop.

We use AI agents to predict, detect, and resolve issues before they become incidents. Fully integrated with Ops.ai and 4Sight.

What the agents do:

• Monitor telemetry across infra and apps
• Spot anomalies with ML-driven time-series forecasting
• Run auto-resolution playbooks (restart, isolate, escalate)
• Continuously learn from outcomes to reduce noise

Agentic IT Ops Framework:

Outcome: 60% faster incident triage, 80% reduction in false positives, 40% lower MTTR, Always-on improvement via closed-loop learning