Agentic Solutions
Implement Agentic AI
& Tool Integrations
Move beyond chatbots. Deploy Autonomous Agents that can plan, reason, and execute tasks across your enterprise systems.
Dual-Memory Architecture
State & Context Management
Short-Term Memory (Context)Active Session
Long-Term Memory (Vector DB)Episodic Storage
Past Interactions
Vector Store
Agents automatically embed and store key facts from conversation history (e.g., user preferences, project details) to maintain continuity across sessions.
Namespace: user_123TTL: Indefinite
Problem Solving
Advanced Reasoning Systems
Agents are more than just LLMs; they are reasoning engines. We implement the ReAct (Reasoning + Acting) pattern, enabling models to break down complex user requests into discrete logical steps, execute tools, and observe results before formulating a final answer.
- Chain-of-Thought (CoT) Prompting
- Self-Correction Loops
- Dynamic Planning
Reasoning Engine (ReAct)
Chain-of-Thought Problem Solving
THOUGHT
Processing
The user wants to compare sales of 'Product A' vs 'Product B' for Q1. I need to fetch data for both products first.
ACTION
ToolCall: Database.query('SELECT sales FROM transactions WHERE product IN (A, B) AND quarter = Q1')
OBSERVATION
Result: [{product: 'A', sales: 1500}, {product: 'B', sales: 2100}]
ANALYSIS
Product B sold 600 units more than A. That is a 40% difference.
FINAL ANSWER
Product B outperformed Product A by 40% in Q1 (2100 vs 1500 sales).
Multi-Agent Swarm
Model Coordination & Routing
Supervisor
Coder
Researcher
Reviewer
Dynamic Delegation: The Supervisor decomposes the task and routes sub-problems to the most capable specialist.
Agent Coordination
Multi-Agent Orchestration
For complex enterprise tasks, a single agent is often insufficient. We architect Agent Swarms where a Supervisor Agent delegates sub-tasks to specialized experts (e.g., a "Coder" for SQL, a "Writer" for email). This parallelization increases accuracy and capability.
Tool Integration (MCP)
Intelligent Tool Use
Registered Tools (Model Context Protocol)
query_database
Execute SQL on read-only replica
MCP Server
search_web
Bing/Google Search Wrapper
API
calculator
Python math evaluator
Function
Runtime Log
Waiting for agent invocation...
Mission Control & Safeguards
Controlled Execution
Operational Boundaries
Recursion Limit
Max 5 loops per task
ACTIVE
Budget Cap
$0.50 per execution
ACTIVE
Tool Whitelist
Read-Only Access for Level 1
ACTIVE
Sensitive Action Detected
Action:API_POST /v1/refund
Amount:$5,000.00
Confidence:82% (Threshold 90%)