AgentHack submission type
Enterprise Agents
Name
Onyekachi John
Team name
BizPulse AI
Team members
@Dharanidhar Sunkari @Badesab Shaik
How many agents do you use
Multiple agents
Industry category in which use case would best fit in (Select up to 2 industries)
Banking and financial services
Finance
Complexity level
Intermediate
Summary (abstract)
BizPulse AI – Strategic Decision-Making Powered by Agentic AI
BizPulse AI leverages Agentic AI architecture to deliver a real-time business advisory system for executives.
At its core, a central intelligent agent interprets natural language queries (voice or text) and dynamically delegates them to specialized sub-agents like Sales Agent or Finance Agent. These agents analyze enterprise data and return instant, actionable insights—all within seconds.
Fully built on the UiPath platform, this solution automates the complete query-to-decision pipeline with zero FTE involvement. With modular scalability and seamless integration, BizPulse AI showcases the power of Agentic AI in orchestrating intelligent, autonomous decision-making for the enterprise.
Detailed problem statement
Current Situation:
In many businesses, strategic decision-making relies heavily on siloed reports, spreadsheets, and delayed communications between teams (e.g., sales and finance departments). Business executives and managers often need to manually compile, cross-reference, and interpret data to support key decisions such as:
Forecasting sales pipelines
Evaluating financial risks
Assessing operational KPIs for planning
Even with basic automations (e.g., attended bots, dashboards), the process is linear, fragmented, and requires human intervention at every stage to synthesize insights from disparate systems (CRM, ERP, spreadsheets, BI tools).
Manual Efforts Currently Involved:
Manually querying multiple systems (CRM, finance systems, Excel sheets)
Cross-checking different reports and KPIs
Email or chat-based communication loops for clarification
Creating final reports by copy-pasting data
Decentralized handling of sales vs finance KPIs
Challenges in Current System:
Lack of real-time decision readiness — insights lag behind data availability.
Fragmented workflows — individual bots may exist, but are not autonomous or decision-capable.
No orchestration — users must manually orchestrate processes.
No true ‘agent’ behavior — current automations wait for human initiation or guidance.
Overload of manual judgment — humans must interpret even basic insights.
Detailed solution
We propose to build a Strategic Decision-Making Agent: an autonomous, agentic UiPath-powered solution designed to interpret queries (voice/text), autonomously decide which sub-processes to trigger, gather data, and provide direct, actionable recommendations.
Key Features of Our Solution:
Voice & Text Input: Users can ask questions like “What’s our projected Q3 revenue for Product X?” via a UiPath App or WhatsApp/Teams integration.
NLP-driven Intent Detection: The main agent parses the query, identifies the domain (Sales or Finance), and routes to the appropriate Sub-Agent.
Autonomous Sub-Agent Execution:
SalesAgent → generates forecasts, summaries from CRM, sales records, and predictive models.
FinanceAgent → analyzes cost structures, risk factors, and project expenses.
Decision-Making Layer: The MainAgent reasons over gathered data and presents synthesized insights.
Real-Time Output: Results shown via UiPath Apps or integrated into emails/reports, ready for executive decision.
Learning Feedback Loop: Feedback from user decisions or corrections improves future responses.
Agentic Automation Principles Used:
Principle How it Applies
Perception Parses natural language inputs (text/voice)
Reasoning Chooses correct agents based on context
Decision-Making Combines outputs, offers actionable insights
Autonomy Runs without human prompts after query intake
Learning Feedback loop to refine intent mapping & responses
Why UiPath Specifically?
UiPath Agent Builder to encapsulate the main and sub-agents.
AI Center to manage NLP models and predictive forecasting models.
Apps for an interactive front-end experience.
Data Service to store interactions, feedback, historical data.
Seamless integration with existing UiPath Automations/Workflows already in use by many enterprises.
Demo Video
Expected impact of this automation
Transformative Outcomes:
Time Savings: Reduce the time to generate critical business insights from days to minutes.
Decision Accuracy: Fewer manual mistakes; decisions driven by consistent, contextualized data.
Scalability: The architecture supports adding new domains (e.g., HR, operations) with new sub-agents in the future.
Productivity Boost: Executives and analysts can shift from data-gathering tasks to strategic thinking.
True Agentic Automation in Practice: A hands-free, real-time strategic advisor that fits perfectly with UiPath’s future vision of autonomous agents transforming work.
Social/Organizational Impact:
Breaks organizational silos by providing a unified intelligence system.
Empowers even non-technical decision-makers to get advanced business insights.
Reduces dependency on manual BI efforts or fragmented RPA bots.
UiPath products used (select up to 4 items)
UiPath Agent Builder
UiPath Apps
UiPath Automation Cloud™
UiPath Data Service
UiPath Orchestrator
UiPath Robots
UiPath Studio Web
Automation Applications
Data Fabric
Integration with external technologies
Open AI
Agentic solution architecture (file size up to 4 MB)
Sample inputs and outputs for solution execution
Input :
- “What is the total sales forecasts for Q3 2025?”
- “Can you give me an overview of our current operating expenses?”
- “How did customer acquisition trends change in the last quarter?”
Outputs:
Status: [Success or Failed]
Intent: [Finance, Sales, or General]
Sub-Agent Used: [FinanceAgent, SalesAgent, or None]
Original Query: [User’s original question]
Clarification Needed: [Yes or No]
Final Response: [Your detailed response to the query]
Follow-Up Required: [Yes or No]
Escalate: [Yes or No]