Agentic AI Solutions

Trusted by:

Daffodil software clients - Maya Md
Daffodil software clients- Reserve Bank on India (RBI)
Daffodil software clients - Pramerica Insurance
daffodil client - samsung
scale ai logo
Daffodil software clients - Denso

Maximize business performance with Agentic AI solutions

Values we add to the businesses with our Agentic AI Solution Development

Unlock operational efficiency with enterprise-grade agentic AI development services

Agentic AI consultation

Assess your business processes, identify operations that can be automated, and create a strategic roadmap for implementation with our agentic AI experts. We help prioritize use cases, calculate ROI potential, and design a phased approach that aligns with your business objectives and technology capabilities.

Proof of Concept and prototyping

Accelerate your agentic AI development journey with our Proof of Concept (PoC) and prototyping services. We develop prototypes and minimum viable agents to test ideas efficiently, ensuring feasibility before full-scale implementation. 

Custom agentic AI development

Build tailored AI agents that understand your specific industry challenges and business rules. Our developers combine large language models (LLMs), reinforcement learning, and custom algorithms to create AI systems that perform complex tasks autonomously with minimal human oversight.

Agentic AI integration services

Integrate your new AI agents seamlessly with existing software, databases, and third-party services. Our agentic AI development services ensure smooth data flow, secure authentication, and consistent performance across your entire technology ecosystem without disrupting operations.

Agentic AI testing services

Ensure reliability and performance of autonomous systems with our agentic AI development company. We rigorously validate AI agents across real-world scenarios, edge cases, and decision-making processes to guarantee accuracy, safety, and consistency, minimizing risks and maximizing trust in your AI-driven operations.

Agentic AI training and optimization

Improve agent performance through continuous data feedback loops and fine-tuning. Our specialists implement systematic testing protocols, performance analytics, and optimization techniques that ensure your AI solutions continuously improve accuracy, efficiency, and business impact.

Maintenance and support

Entrust your agentic AI infrastructure to our expert team with 24/7 monitoring, maintenance, and troubleshooting. Our agentic AI development company handles all technical aspects, including model updates, security patches, performance optimization, and scaling during peak demand periods.

Hire agentic AI developers

Empower your business with our expert agentic AI developers who craft intelligent, autonomous AI agents tailored to your needs. Our specialists develop agentic AI systems that make proactive decisions, optimize workflows, and drive efficiency. 

Turn complex operations into autonomous workflows with AI agents

Automate every department with intelligent agentic AI solutions

servic-img

Customer support

  • Autonomous customer support that independently resolves inquiries across multiple channels 24/7
  • Independent sentiment analysis agents that monitor customer emotions and adjust interaction strategies
  • Escalation management AI agents that determine when human intervention is required
  • Self-managing knowledge base agents that continuously update and improve support documentation
servic-img

IT and technology

  • Cybersecurity monitoring to detect threats and implement protective measures
  • Self-directed system maintenance to optimize performance and prevent downtime
  • User access control that provisions accounts and manages permissions
  • Independent IT helpdesk agents to resolve technical issues and guide users through solutions
servic-img

Quality assurance and control

  • Defect detection AI agents that monitor quality 
  • Self-directed process optimization for workflow analysis and efficiency improvements
  • Autonomous testing protocol agents that execute quality validation procedures
  • Self-managing documentation agents that maintain quality records and audit trails
servic-img
  • Automated contract analysis and compliance verification
  • Real-time monitoring for regulatory adherence
  • AI-powered risk assessment and mitigation
  • Knowledge management with agentic AI capabilities
servic-img

Procurement and purchasing

  • Spend analysis to monitor purchasing patterns and identify cost savings
  • Independent market analysis agents that monitor pricing trends and supplier capabilities
  • Independent market analysis agents that monitor pricing trends
servic-img

Supply chain and operations

  • Inventory management that independently monitors stock levels and triggers reorders
  • Supplier management AI agents that evaluate vendor performance 
  • Self-managing warehouse optimization to organize layouts

Build industry specific AI agents with us

Customer success stories across AI ecosystem

Client experiences that reflect the impact of our technical expertise

Crafting intelligent AI agents: the journey from concept to deployment

services

Purpose and goal definition

  • Define agent purpose: Identify autonomous tasks and decision-making scenarios the agent will handle.
  • Set agent goals: Establish clear, measurable objectives aligned with business outcomes.
  • Map agent boundaries: Determine the extent of autonomy- what decisions the AI agent can make independently.
  • Design agent persona: Craft the agent’s identity, tone, behavior, and interaction style (especially for LLM-based agents).

Context mapping

  • Set agent environment: Define the physical or digital space in which the agent operates, including data sources, API development and integration, user interfaces, and more.
  • Set contextual constraints: Establish operational, ethical, and regulatory constraints.

Agent architecture design

  • Select architecture type: Choose between LLM-based, RL-based, symbolic, or hybrid agents.
  • Define perception and action layers: Determine how the agent will perceive input and act upon it.
  • Design planning and reasoning modules: Architect how the agent makes multi-step decisions or plans actions over time.
  • Integrate memory and feedback loops: Decide on short-term and long-term memory mechanisms.

Intelligence training and simulation

  • Data preparation: Gather and preprocess data (structured, unstructured, domain-specific).
  • Train core models: Use supervised, unsupervised, reinforcement learning, or fine-tuning on foundational models.
  • Simulate agent scenarios: Run the agent through real-world or synthetic tasks to refine behaviors.

Integration and interfacing

  • Connect to existing systems: Ensure seamless integration with enterprise software, APIs, and user interfaces.
  • Enable multi-modal inputs: Allow the agent to work with text, voice, vision, or sensor data as needed.
  • Ensure fail-safes: Implement human-in-the-loop mechanisms for critical interventions.

Deployment

  • Deploy to production: Launch the agent in the target environment-cloud, edge, or on-prem.
  • Enable self-optimization: Implement mechanisms like RLHF (Reinforcement Learning with Human Feedback) or online learning.
  • Monitor behavior and KPIs: Use analytics dashboards to track agent performance and anomalies.

Ongoing support

  • Feature expansion: Add new capabilities as business needs grow.
  • Cross-agent collaboration: Enable multi-agent systems for complex workflows.
  • Ongoing support and maintenance: Get end-to-end support for your AI agent.

Tools and technologies that power the development of scalable and intelligent AI agents

As a trusted agentic AI development company, we use a robust tech stack designed to accelerate innovation, enhance decision-making, and enable intelligent automation across your business. Our technology choices are driven by the need for scalability, adaptability, and real-time performance, ensuring that the AI agents we build deliver tangible results, integrate seamlessly with your systems, and continuously evolve to meet changing business demands.

Watch our podcast on Agentic AI

Listen to our host Anmol Satija and Jesse Anglen, CEO of Rapid Innovation as they explore how Agentic AI is redefining customer service, streamlining operations, and enhancing decision-making for tech leaders.

Watch now

 

Why Daffodil Software

Recognized excellence, proven customer satisfaction

Daffodil software clients - Everest Group

Categorized as an aspirant in global PEAK Matrix assessment

Daffodil software clients - Gartner

Recommended vendor for custom software development services

Daffodil software clients - Frost & Sullivan

Mentioned as a company to watch in the AI space

Daffodil software clients - Zinnov Zones

Categorized as a leader in digital engineering services

25+

years of software engineering excellence

150+

global clientele

4.8

Avg CSAT score

95%

customer retention rate

Frequently asked questions (FAQs)

How do agentic AI solutions differ from traditional AI?

Traditional AI responds to specific commands and questions. On the other hand, Agentic AI is much more independent. It can identify what needs to be done, create plans, adapt when things change, and use various tools to reach goals. It’s like having a digital employee rather than just a smart calculator or search engine.

Creating AI agents involves designing how they’ll think and work, connecting them to the right AI models, adding tools they can use, building in safety measures, and testing everything thoroughly. The process requires expertise in AI technology, software development, and understanding your specific business needs and workflows.

Less advanced agentic AI solutions cost $25,000-$100,000. More advanced systems with custom features and multiple business system connections range from $150,000-$500,000+. Ongoing costs for maintenance and improvements usually add 20-30% yearly. 

Basic agentic AI solutions take about 2-3 months to build. Mid-level systems that connect to several of your business tools need 4-6 months. Complex enterprise solutions with advanced capabilities and extensive connections to your existing systems typically require 6-12 months from planning to full deployment.

Your business can connect AI assistants to existing systems through direct API links, custom web dashboards, workflow automation tools, or extensions to your current software. We’ll recommend the best approach based on your existing technology, security needs, how employees will use it, and which business processes need improvement.

Common challenges include ensuring reliable performance across different situations, connecting to all necessary business systems, addressing security concerns, creating proper oversight rules, getting employee buy-in, providing adequate training, handling unusual cases effectively, and maintaining the right balance between AI independence and human control.

Successful AI assistants need regular updates to add new capabilities, performance monitoring, expansion to handle new tasks, fine-tuning to maintain effectiveness, security updates, user training, and periodic reviews to keep everything running smoothly. Ongoing support ensures your AI systems continue to deliver value as your business needs change.