TRISLAA
AI & Data/Agentic AI Systems

Agentic AI
Systems

Deploy autonomous AI agents that reason, plan, and execute complex workflows—transforming how work gets done across your organization.

70-80%
Time savings on routine knowledge work
85%
Of tasks automated with agent systems
24/7
Continuous autonomous operation
10x
Productivity improvement for complex tasks

Beyond Chatbots: The Agentic AI Revolution

Traditional AI assistants respond to questions. Agentic AI systems take action. They can break down complex tasks, make decisions, use tools, call APIs, and execute multi-step workflows with minimal human intervention—like having an always-on expert team member.

Think of agentic AI as giving your AI an operating system—the ability to plan, reason about steps, use tools when needed, handle errors, and iterate until a task is complete. This represents a fundamental shift from passive assistance to active task execution. Our clients implementing agentic AI see 70-80% time savings on routine knowledge work, freeing human workers to focus on high-value strategic activities that require creativity and judgment.

Agent Capabilities

Four pillars of enterprise agentic AI implementation

Multi
Agent Orchestration
Collaborative Intelligence

Multi-Agent Orchestration

Just as expert teams in your organization have specialists who collaborate, multi-agent systems deploy multiple AI agents—each with specific expertise—that work together, delegate tasks, and synthesize results. This enables solving problems far more complex than any single agent could handle.

Supervisor Pattern: A coordinator agent delegates tasks to specialist agents and synthesizes their outputs
Hierarchical Teams: Agents organized in teams with leads that manage coordination and quality control
Debate & Consensus: Multiple agents propose solutions, critique each other, and reach consensus

Example: Financial Research Agent System

Research Coordinator: Breaks down request into sub-questions

Data Gathering Agent: Collects financial data from multiple sources

Analysis Agent: Performs quantitative and qualitative analysis

Risk Assessment Agent: Evaluates risks and red flags

Writing Agent: Synthesizes findings into investment memo

Result: 4-hour research task completed in 30 minutes

Function Calling

Tool-Using Agents

The real power of agentic AI emerges when agents can take actions—not just provide recommendations. We implement secure function calling that allows agents to query databases, update records, send notifications, and interact with business applications, all with appropriate governance and controls.

Database Queries: Search, filter, and aggregate data from SQL/NoSQL databases
API Calls: Interact with CRM, ERP, project management, and custom business applications
Document Processing: Read, parse, and extract information from various file formats
Email & Notifications: Send communications and alerts based on findings and actions

Security & Governance:

All tool usage includes validation, approval workflows for sensitive actions, comprehensive audit logging, and role-based access controls. Agents never have unlimited access—we implement guardrails and human-in-the-loop patterns for critical operations.

Customer ServiceSales AssistantIT OperationsFinance Agent
Tools
Function Calling
Think
Advanced Reasoning
Intelligent Planning

Advanced Reasoning & Planning

Effective agents don't just execute pre-defined workflows—they reason about problems, generate plans, evaluate options, and adapt based on results. We implement sophisticated reasoning patterns that dramatically improve agent reliability and capability for complex tasks.

Chain-of-Thought (CoT)

Guide agents to think through problems step-by-step, showing their reasoning process. Dramatically improves accuracy on complex tasks.

ReAct (Reasoning + Acting)

Agents alternate between reasoning about what to do next and taking actions. They observe results and adjust their approach dynamically.

Tree of Thoughts

Explore multiple reasoning paths simultaneously, evaluate them, and pursue the most promising approach. Like parallel thinking.

Planning Capabilities

✓ Task decomposition into manageable subtasks
✓ Dependency management and sequencing
✓ Error handling and alternative approaches
✓ Progress tracking and plan adjustment
Governance & Control

Human-in-the-Loop & Governance

Not every task should be fully autonomous. We design systems with appropriate checkpoints where human judgment is required—approvals for sensitive actions, verification of high-stakes decisions, and oversight of agent behavior. This balances autonomy with control.

Approval Workflows: Agents can propose actions but require human approval for execution on sensitive operations
Confidence Thresholds: Automatic execution when confident, human review when uncertain
Comprehensive Audit Trails: Complete logging of all agent decisions and actions for compliance
Escalation Paths: Clear handoff to humans when agents encounter edge cases or ambiguity

Continuous Learning

Human corrections and feedback loops continuously improve agent performance. The system learns from every intervention, becoming progressively more autonomous over time while maintaining safety.

HITL
Human Oversight

Agent Systems in Action

Real-world implementations delivering transformative results

Financial Services

Loan Processing Agent System

Large Regional Bank

Challenge

Manual loan application review taking 5-7 days with inconsistent decision quality and high operational costs

Solution

Multi-agent system with document verification agent, credit analysis agent, fraud detection agent, compliance checker, and decision synthesizer working collaboratively

Results

  • 85% of applications processed in under 2 hours
  • 40% operational cost reduction
  • Improved consistency and compliance
Healthcare

Prior Authorization Agent

Health Insurance Provider

Challenge

Prior authorization requests taking 3-5 days, causing physician frustration and delayed patient care

Solution

Agent reviews medical records, checks policy coverage, evaluates medical necessity criteria, auto-approves clear cases, flags complex cases for medical director review

Results

  • 60% auto-approval rate
  • Under 4 hour turnaround for auto-approved cases
  • Higher physician satisfaction, better patient outcomes
Technology

Customer Support Agent

SaaS Company

Challenge

Support team overwhelmed with tier-1 tickets, slow response times, scaling costs with growth

Solution

Agent handles common inquiries, accesses account data, performs troubleshooting steps, resolves tickets or escalates with full context to human agents

Results

  • 75% of tier-1 tickets auto-resolved
  • 90% customer satisfaction maintained
  • Support team focused on complex issues

Implementation Methodology

Systematic approach to deploying autonomous agents

01

Use Case Definition

1 week

Identify high-value processes suitable for agent automation. Define success metrics and ROI model.

Key Deliverables

  • Process analysis
  • Use case prioritization
  • Success metrics
  • ROI projection
02

Agent Design

2-3 weeks

Design agent architecture, tool integrations, reasoning patterns, and approval workflows.

Key Deliverables

  • Agent architecture
  • Tool mappings
  • Workflow design
  • Prototype demo
03

Pilot Deployment

4-6 weeks

Deploy with limited scope. Monitor performance, gather feedback, refine agent behavior.

Key Deliverables

  • Pilot deployment
  • Performance metrics
  • User feedback
  • Refinements
04

Production Scale

6-8 weeks

Expand to full production with monitoring, governance, and continuous improvement.

Key Deliverables

  • Production rollout
  • Monitoring setup
  • Governance controls
  • Training program

Ready to Deploy Autonomous Agents?

Let's identify processes where agentic AI can deliver transformative productivity improvements and free your team for strategic work.

70-80%
Time Savings
85%
Tasks Automated
24/7
Operation