Services Agentic AI · 10+ years · 30+ enterprise programs

Agentic AI Engineering:
Better Operational Decisions. Automatically.

Infarsight Agentic AI engineering builds the decision layer that sits between your operational data and the actions your business needs to take, closing the gap between operational event and automated response, at enterprise scale.

What is Agentic AI?

Agentic AI refers to AI systems that autonomously perceive operational signals, reason across contextual data and execute decisions across connected enterprise systems, without requiring human intervention at each step. Unlike AI that produces recommendations, agentic systems close the loop: they act, escalate and learn from operational outcomes.

Microsoft AI Partner ISO 27001:2018 Model-Agnostic LangChain · LangGraph · AutoGen Human-in-the-Loop by design
10+
Years of AI & ML delivery
30+
Operational AI programs delivered
10×
Faster event-to-action decisions
−80%
Reduction in manual coordination
Why Infarsight for Agentic AI

We Build Production Decision Agents.
Not AI Demos or Proof-of-Concepts.

Decision Agents, Not AI Demos

Every agent we build has a defined operational decision to make, a measurable outcome to drive and a governance framework that keeps humans in control. We don't build AI for its own sake.

Operational Context Is Our Advantage

We understand Travel, Ports and Mobility deeply. Our agents are trained on the operational logic of industries we've been embedded in for over a decade, not on generic enterprise patterns.

The Full Stack — Connected

Our agents sit between Infarsight Data Engineering and Product Engineering. They receive decision-ready signals and execute into operational platforms, all built by us, all connected.

Governance Built In From Day One

Human-in-the-loop controls, explainability, audit trails and drift monitoring are designed into every agent we build, not added after a governance review flags a risk.

What is Agentic AI

An Agentic AI system doesn't
just process data.

It perceives a situation, reasons across available context, decides on an action and executes, or escalates when human judgment is needed.

01 PERCEIVE

Ingests real-time signals

From operational systems, events, anomalies, thresholds and alerts, the moment they occur.

02 REASON

Applies LLM-powered reasoning

Across context, rules, constraints and operational goals, not hard-coded IF/THEN logic.

03 DECIDE

Selects the optimal action

From available options, or flags for human review when the decision requires judgment.

04 ACT

Executes in connected systems

Booking, dispatch, notification, reroute, alert, the decision lands in production, not a report.

5 Service Lines

Each service line has defined inputs,
reasoning models and measurable outputs.

SERVICE LINE 01

Agent Design & Orchestration

Designing the agents, orchestration layer and tool ecosystem that powers autonomous operational decision-making.

LangChain / LangGraphAzure OpenAIAutoGenSemantic KernelOpenAI Assistants API
What we deliver
  • Single & multi-agent architectures
  • Agent role & responsibility design
  • Tool and API integration layer
  • Prompt engineering & LLM selection
  • Orchestration framework design
  • Agent-to-agent communication protocols
Business outcomes
  • Agents that handle real operational decisions
  • Reduced manual coordination overhead
  • Scale decision capacity without headcount
  • Faster response to operational exceptions
  • Foundation for autonomous operations
SERVICE LINE 02

Decision Intelligence

Encoding operational knowledge into agents that make the right call, consistently, at the speed the operation demands.

Azure OpenAILangGraphVector databasesRetrieval-Augmented Generation
What we deliver
  • Decision model design
  • Policy & constraint encoding
  • Contextual reasoning across multiple systems
  • Closed-loop action triggers
  • Scenario simulation & outcome weighting
How it works
  • Signal detected in operational system
  • Agent pulls live context across systems
  • LLM weighs options against constraints
  • Decision executed or escalated to human
SERVICE LINE 03

Human-in-the-Loop Systems

Keeping humans in control where it matters most. Agentic AI without human oversight is a risk, but human oversight without design is a bottleneck.

Escalation designConfidence thresholdsAudit trailsOverride controls
What we deliver
  • Escalation framework design
  • Confidence thresholds & override controls
  • Feedback & retraining loops
  • Full audit trail, every decision, logged and explainable
The control spectrum
  • AUTO — Agent decides & acts for high-confidence, low-risk decisions
  • CONFIRM, Agent proposes, human approves in one click
  • HUMAN, Agent surfaces options; human makes final call on high-stakes decisions
SERVICE LINE 04

Agent Ops & Governance

Keeping agents reliable, transparent and compliant, in production, over time. Governance is not an afterthought; it is designed into every agent we build from day one.

LangSmithAzure AI StudioMLflowArize / Whylabs
What we deliver
  • Agent monitoring & alerting dashboards
  • Explainability, full reasoning chain logged per decision
  • Compliance & audit trails
  • Model drift detection & retraining triggers
Why it matters
  • Anomalies surface before operations are impacted
  • Every decision queryable by regulators or auditors
  • Agent behaviour stays aligned with business intent
  • Production AI that builds trust over time
SERVICE LINE 05

Operational Integration

Connecting agents to the systems they need to perceive, decide and act, without replacing the infrastructure already in place.

ERP / CRM connectorsAction execution APIsEvent stream ingestionIoT & sensor feeds
The three layers
  • Data Layer, Data Engineering pipelines provide decision-ready signals to the agent
  • Agent Layer, Agentic AI practice handles perception, reasoning, decision and escalation routing
  • Action Layer, Product Engineering platforms execute the agent's decisions in production
What we connect
  • Booking & reservation systems
  • Dispatch & scheduling platforms
  • Notification & communications
  • Workflow & task management systems
  • IoT, telemetry & sensor feeds
Technology ecosystem

Model-agnostic, architecture-driven.

We are not tied to any single AI provider. We select foundation models, frameworks and retrieval systems based on the decision context, latency requirements and governance needs of each use case.

FOUNDATION MODELS
  • Azure OpenAI / GPT-4o
  • Anthropic Claude
  • Mistral / Llama
  • Google Gemini
AGENT FRAMEWORKS
  • LangChain / LangGraph
  • Microsoft AutoGen
  • Semantic Kernel
  • OpenAI Assistants
MEMORY & RETRIEVAL
  • Azure AI Search
  • Pinecone
  • pgvector
  • Redis Vector
OPS & GOVERNANCE
  • LangSmith
  • Azure AI Studio
  • MLflow
  • Arize / Whylabs
Industry application

Agentic AI Decision Systems Purpose-Built for
Travel, Ports, Mobility and Airlines.

Travel & Hospitality

  • Disruption management agent — auto-rebook, reroute & rehouse at scale
  • Guest services agent, resolves complaints, upgrades and loyalty queries
  • Revenue management agent, triggers dynamic pricing in real time
  • Crew & resource agent, rebalances assignments to schedule changes

Ports & Logistics

  • Berth conflict agent — resolves scheduling conflicts before they impact ops
  • Gate management agent, optimises container flow by dwell time & priority
  • Customs & compliance agent, flags clearance risks before vessels berth
  • Port throughput agent, reallocates resources during anomalies & peak load

Fleet & Mobility

  • Predictive maintenance agent — predicts failures from telemetry before breakdowns
  • Dispatch optimisation agent, reallocates fleet by demand, health & SLA
  • EV charging agent, manages charging schedules & fault resolution at scale
  • Driver safety agent, monitors behaviour and triggers interventions

Airlines

  • Operations control agent — manages turnaround conflicts & gate assignments
  • Passenger disruption agent, handles rebooking, hotels & comms end-to-end
  • Crew management agent, rebalances pairings after delays & cancellations
  • Revenue agent, triggers pricing, upgrade & overbooking actions
Client outcomes

Measurable Results from
Infarsight Agentic AI Programmes.

10×

Decision Speed

Operational decisions that previously took 20–60 minutes are executed by agents in under 2 minutes, across disruption, dispatch and scheduling workflows.

−80%

Manual Coordination

Agents handle the volume of operational exceptions that previously required coordinator intervention, freeing teams for judgment-intensive work.

95%

TripSight Resolution Rate

TripSight — Infarsight's proprietary travel operations accelerator, resolves 95% of passenger disruption cases without human involvement.

Near-zero

Decision Latency

Continuous agent operation eliminates the wait time between operational event and corrective action, the gap where cost and customer impact accumulate.

How we engage

The Agentic AI workflow.

From operational decision problem to production AI agent, in a governed, risk-managed process.

01

Discover

Decision mapping workshop, agent candidate scoping, data & signal audit, risk & governance brief. 1–2 weeks.

02

Design

Agent architecture, decision boundary definition, HITL framework design, tool & API mapping. 2–3 weeks.

03

Build

Agent development, integration delivery, sandbox testing, HITL workflow build. 4–10 weeks.

04

Operate

Decision monitoring, escalation management, quality scoring, governance reporting. Ongoing.

05

Evolve

Decision scope expansion, agent retraining, new integrations, performance optimisation. Continuous.

Ready to close the decision gap?

We start with a Decision Mapping Workshop, identifying the highest-value operational decisions in your business, mapping the signals available and designing the first agent use case.

Book a Decision Mapping Workshop →
01 Decision Mapping Workshop
02 Agent Architecture & Governance Design
03 Pilot Agent Build & Deployment