Agentic AI Development Services
Transform your operations with agentic AI solutions that are tailored to your business needs and goals while effectively managing your AI risk.
Accelerate & scale With agentic ai
Our agentic AI development services
Agent design &development
Ensure optimal individual and multi-agent performance, enhance productivity, and enable seamless agent integration with value-driven, tailored agent design and development.
Multi-agent orchestration
Minimize human errors and enhance productivity by augmenting complex tasks and decision-chains with multi-agent deployment and seamless orchestration.
Human-in-the-loop systems
We help you stay compliant and balance human expertise and oversight with agentic automation by developing efficient, auditable, and explainable HITL agentic AI systems.
Architecture assessment & modernizations
Optimize modernization effort and cost while maximizing agentic AI benefits for your workflows with assessment-based, goal-aligned strategies for architectural revamps.
AgentOps & AI agent infrastructure
Enable transparent agentic deployments, maximize AI observability, ensure traceability, and mitigate hallucination with AgentOps, future-proofing your agentic AI models.
AI-ready data architecture
Maximize agentic AI productivity and efficiency with a robust data infrastructure that ensures optimal data availability, accessibility, and transformation for AI agents.
Adoption & change-management
Streamline change management with training, non-disruptive designs, and agentic AI integration consulting services tailored to your AI goal and readiness gaps.
Agentic AI governance& security
Enhance productivity of sensitive tasks and enable compliant agentic operations by embedding security and governance controls in agent architectures and orchestrations.
Agentic AI scaling & evolution
Seamlessly scale agentic AI capabilities for more complex, high-volume tasks across enterprise workflows with modular builds and intelligent orchestration.
Our impact in numbers
1400+
Developers & AI experts
400+
Projects completed successfully
200+
Enterprise clients across industries
20+
Developers & AI experts
Why enterprises choose us for agentic AI development services
AI development
leadership
Our advanced AI engineering, AI-first architectures, scalable agent builds, and model orchestration make us a valued agentic AI partner for enterprises.
Orchestration expertise
Enable complex, agent-driven workflows through advanced orchestration, using the model context protocol (MCP) to ensure seamless context sharing.
Frictionless AI integration
Deep legacy, cloud, middleware, and data infrastructure expertise allow us to build agentic AI systems that seamlessly integrate with your business.
Scalable & resilient builds
Implement agentic AI models capable of evolving with changing parameters, leveraging modular, decoupled, and orchestrated agentic workflows.
Strong data foundations
Our advanced data engineering capabilities allow us to build a strong data foundation for agentic AI models, while implementing strict privacy controls.
Rapid delivery cycles
With agility at our core, we build and help enterprises adopt tailored agentic AI systems rapidly, driving competitive advantage and adaptability.
Governance & security
We enable secure adoptions by keeping pace with evolving AI regulations and adhering to frameworks like NIST and ISO 42001.
Diverse industry experience
Ensure seamless agentic integration and regulatory compliance by leveraging our comprehensive and diverse industry knowledge.
Explore how model context protocol (MCP) enables secure, scalable agentic AI solutions
Benefits of implementing agentic AI
Productivity & efficiency
By automating complex processes, seamlessly coordinating handovers, and enabling data-driven decision making, agentic AI serves as a potent productivity multiplier.
Data-driven decision-making
Agentic AI replaces rule-based decision-making with data-driven autonomy and adaptive decision-making with much broader and richer applicability.
Human error & bias mitigation
Bias risk in AI agents is systematically mitigable, and they significantly reduce human errors, making business processes more robust and reliable.
Operational agility
Agentic AI systems with built-in feedback loops self-optimize and may adapt faster to changing requirements than humans, increasing operational agility.
Governance & visibility
From automated activity logs to decision chains, agentic AI deployments offer increased visibility of operations and decision-making, enabling better governance and proactive optimization.
Our approach to agentic AI development
1.Goal evaluation
We start by evaluating your agentic AI goals in the context of your operational needs, goals, and broader AI goals, and identifying specific processes that may benefit from agentic AI.
2.Technical assessment
A comprehensive technical assessment of your existing data and overall digital infrastructure for its AI adoption readiness to define the scope of work.
3.Tool & framework selection
Optimal agentic AI development tools and frameworks are selected based on your cloud environment, existing operational needs, and future scalability projections.
4.Design & development
Individual AI agents and orchestrated multi-agent systems are developed and tested for their individual and collective functionality. Security and governance controls are embedded.
5.Deployment & integration
Tested agent AI systems are strategically deployed and tested again in production for performance, operational friction, external access, and security/compliance vulnerabilities.
6.Change management
We help enterprises redefine their workflows around agentic AI deployments for optimal performance, scalability potential, and adopt the best change management practices.
7.Monitoring & optimization
We monitor the behavior of agentic AI systems for drift, external calls, self-optimization, etc., and make modifications to individual agents and multi-agent orchestration for optimal results.
Leverage agentic AI that’s built to evolve & scale
Unlock massive productivity gains with agentic AI, securely, compliantly, and pragmatically with 10Pearls.
Industry use cases for agentic AI
Financial Services
- Fraud detection and case resolution
- Loan and insurance underwriting
- Trading and portfolio management
- KYC and AML automation
Healthcare
- Prior authorization and claims processing
- Clinical decision support systems
- Staff administrative tasks automations
- Patient onboarding and coordination
Education
- Personalized learning pathways and tutoring
- Automated grading, assessment, and feedback
- Tailored content generation
- Administrative tasks automation
Technology
- Quality Assurance (QA)
- Agentic software development
- Resource optimization (cloud, compute, etc.)
- IT service management
Energy
- Predictive maintenance
- Grid balancing and optimization
- Energy trading and market optimization
- Renewable power optimization
Telecom
- Energy
- Predictive maintenance
- Grid balancing and optimization
- Energy trading and market optimization
- Renewable power optimization
The state of agentic AI
Agentic AI platforms & frameworks we leverage
AI PLATFORMS
AI FRAMEWORKS
Agentic AI consultancy tailored to your needs
Our agentic AI consulting services can help you make an informed decision about embedding agentic AI into your workflows.
Insights
AI/ML
Understanding the uses of AI in energy sector
This blog explores how AI is transforming the energy sector, the opportunities it offers in various energy domains, and what it takes to run AI on energy data.
AI
Integrating AI with Legacy Systems: Enterprise Guide
Four in five enterprises are struggling to connect AI to the systems they already run. Four proven strategies for bridging that gap without ripping anything out.
AI/ML
Agentic AI in the Telecom Industry
The telecom industry is embracing agentic AI for multiple operational and customer-facing use cases, while navigating legacy systems, integration, and governance challenges.
AI/ML
AI Adoption Challenges and How Enterprises Can Solve Them
Explore the key enterprise AI adoption challenges businesses face, from data and governance to talent and strategy, and discover practical ways to scale AI beyond pilots and drive lasting business value.
AI/ML
Generative AI implementation roadmap for enterprise
Learn how to build a generative AI strategy that aligns investment with business priorities, reduces implementation risk, and creates a path from early pilots to scalable value.
AI/ML
How AI Fraud Detection Works and Where It Still Fails
How AI fraud detection works in real time, which use cases scale first, and where models still fail against AI-powered fraud.
AI/ML
Building Compliant System with Automated Regulatory
Regulatory reporting is high-stakes and error-prone. Learn how to automate reporting and build compliance into every step of the process.
AI/ML
Build and Scale Production ML Pipelines with Databricks MLflow
Building ML pipelines with MLFlow in Databricks can give enterprises already invested in the platform a more governed, repeatable path across the ML lifecycle.
AI/ML
AI in Hospitals: Scaling Pilots to Production
Learn why most hospital AI pilots stall before production, which high-ROI use cases scale first, and how the Define, Integrate, Embed, Operate model closes the gap.
AI/ML
Shadow AI detection and prevention in enterprises
Enterprises today are facing unique AI-related challenges, including shadow AI use. It's imperative that enterprises understand what it is and how to detect and govern it.
Our agentic AI case studies
FAQs about our agentic AI development services
Agentic AI refers to AI-powered systems that can plan, sequence, and execute multi-step tasks based on pre-defined goals with minimal to no human intervention. They can modify their behavior based on external and internal feedback loops, self-optimize, access external resources, and possess at least some degree of autonomy. In the broadest sense, it means any AI system that has the “agency” to pursue a goal without step-by-step human guidance can be considered agentic AI.
The core characteristics of agentic AI include perception, reasoning, objective planning, decision-making, and learning. Some AI leaders also include orchestration as a core characteristic in most multi-agent deployments.
Agentic AI is the broad classification of AI systems with the autonomy to plan and act towards pre-defined goals and feedback loops for self-optimization. While AI agents are the individual units within this model. AI agents are goal-driven components designed to perform specific tasks, use tools, access systems, or handle a defined workflow. They operate with scoped permissions, capabilities, and responsibilities. Multiple AI agents can be connected and orchestrated to achieve more complex agentic AI deployment.
Only if they are designed and deployed without prioritizing governance and security from the beginning. As an ISO 27001 certified company well-versed in AI governance frameworks and regulations, 10Pearls takes a security and governance-first approach to agentic AI software development services. We identify vulnerabilities and risks that different levels of agentic autonomy pose and strengthen the security and governance posture for this expanded threat surface.
Yes. Many multi-agent, orchestrated implementations can fully automate a workflow end-to-end. However, some sensitive situations may require human oversight and decision-making for compliance.
Transform your business with agentic AI
Rethink your operational model and break through your workforce constraints with agentic AI tailored to your business.