Customers expect every interaction to be quick, relevant, and effortless. Yet, fragmented data, growing support queues, and repetitive requests leave service teams stretched thin and customers waiting for answers.
Decision Foundry helps businesses put agentic AI to work across customer service. By connecting data, automating routine tasks, and coordinating workflows, we help teams resolve issues faster, reduce manual effort, and deliver more connected customer experiences.
Rising Ticket Volumes: Growing customer inquiries and repetitive requests overwhelm support teams, making it harder to maintain response times and service quality.
Disconnected Customer Data: Customer details, purchase history, and support records sit across different systems, forcing agents to search multiple platforms for answers.
Slow Resolutions: Manual processes, repeated information gathering, and multiple handoffs delay issue resolution and frustrate customers.
Inconsistent Customer Experiences: Disconnected channels and limited customer context lead to inconsistent responses and fragmented support journeys.
Missed Opportunities: Reactive service makes it difficult to identify recurring issues, anticipate customer needs, and address problems before they escalate.
Increasing Service Costs: Rising support demand puts pressure on teams to handle more requests efficiently without compromising service quality or increasing operational costs.
Help customers resolve routine inquiries, find answers from approved knowledge sources, and access information from connected business systems. Service agents can guide customers through common support processes, respond to frequently asked questions, and escalate complex issues to human representatives with the relevant context.
Automate the initial stages of case management by analyzing incoming requests, identifying issues, prioritizing cases, and routing them to the right teams. These agents can summarize case histories, gather missing information, and initiate approved workflows to reduce manual triage and unnecessary handoffs.
Connect customer service workflows with order management, billing, and account systems to help customers check delivery status, understand invoices, request returns, and access account information. Where permissions allow, agents can initiate approved actions while routing sensitive changes and exceptions for human review.
Bring together customer profiles, purchase history, previous interactions, and open service cases to give support teams a more complete view of each customer. With relevant information available in one place, teams can provide more personalized assistance, reduce repeated questions, and resolve issues with less manual research.
Identify potential service issues, such as delayed deliveries, recurring complaints, or unresolved cases, using available customer and operational data. These agents can flag cases that need attention, trigger approved follow-ups, and help service teams address problems before they escalate.
Reduce repetitive administrative work by summarizing customer interactions, retrieving relevant knowledge articles, updating case records, and coordinating follow-up tasks. These agents help service teams manage queues more efficiently, maintain accurate records, and focus their time on complex customer needs.
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Let's identify the right opportunities to automate workflows, reduce manual effort, and improve customer experience.
Prebuilt AI agents
Prebuilt AI agents are a good fit for common service tasks, such as answering customer inquiries, tracking orders, and routing support requests. They offer a faster starting point when their capabilities align with your existing workflows.
Custom AI agents
Custom AI agents are better suited to business-specific processes, complex integrations, or requirements that prebuilt solutions cannot fully support. They can be designed around your systems, data, business rules, and approval processes.
Decision Foundry evaluates your customer service workflows and technology environment to identify the right approach, whether that means configuring a prebuilt agent, developing a custom solution, or combining both. Explore our Custom AI Agents services
From inquiry to resolution in a few steps. An agent handles the details, so your team can focus on what matters.
The agent interprets the message and identifies the order or delivery issue.
It checks connected systems, delivery status, customer history and policies.
Based on the information and rules, it picks the best next step.
If authorized, it sends the update or starts the workflow. Otherwise, it hands off to a human agent.
The interaction is logged and any follow-up is scheduled or routed.
The result
A more informed customerA more efficient service teamOrder tracking, returns support, product inquiries, and delivery exceptions.
Account inquiries, transaction support, service request routing, and dispute intake, with appropriate verification and controls.
Billing questions, service troubleshooting, plan inquiries, and outage-related communications.
Technical support triage, troubleshooting guidance, subscription queries, and escalation management.
Booking inquiries, itinerary changes, cancellation requests, and disruption support.
Appointment and coverage inquiries, claims status support, and administrative request routing, subject to applicable privacy and compliance requirements.
Identify repetitive requests, workflow bottlenecks, and high-value automation opportunities.
Assess customer data, knowledge sources, and systems to determine integration and automation needs.
Define agent responsibilities, permitted actions, escalation rules, and approval controls.
Build agents, connect systems, and test response quality, accuracy, permissions, and exception handling.
Deploy agents within a defined workflow or channel, validate performance, and refine before scaling.
Track resolution times, escalations, customer satisfaction, and costs to improve agent performance continuously.
Explore Decision Foundry's AI portfolio to learn more about our AI solutions, capabilities, and approach to intelligent automation.
With more than 20 years of experience in data and analytics, Decision Foundry helps organizations connect information across systems and turn it into practical business capabilities.
We help bring together relevant customer, service, and operational data so agents can work with the context required to support more informed interactions.
Our experience across data engineering, CRM, and analytics helps us design solutions that fit into your current technology environment rather than adding unnecessary complexity.
We define clear permissions, approval points, and escalation paths so agents can handle appropriate tasks while people retain control of sensitive decisions and exceptions.
We address the practical requirements of implementation, including data readiness, integrations, testing, deployment, and performance monitoring, to help move promising use cases into operational use.
Every service operation has different customer expectations, processes, and constraints. We tailor the approach to your workflows, systems, and goals instead of applying a one-size-fits-all model.
Talk to Decision Foundry about your customer service priorities. We'll help identify suitable use cases, assess how agents could work with your existing systems, and define a practical path toward implementation.
Talk to Decision FoundryKeep Exploring
A traditional chatbot typically responds to questions using predefined flows or generated answers. An agentic AI solution can also retrieve information from connected systems, plan a sequence of steps, use approved tools, and carry out defined actions. Read our article to understand better AI Chatbots vs. AI Agents: What's the Difference?
It can help gather case history, summarize the issue, identify relevant policies, and coordinate appropriate next steps. Complaints involving sensitive circumstances, exceptions, or significant customer impact should be escalated to a human when required by the organization's rules.
Useful measures include first-contact resolution, average handling time, time to resolution, escalation rates, task completion accuracy, customer satisfaction, and cost per interaction. The right metrics depend on the workflow and should account for service quality as well as efficiency. Agentic AI ROI Measurement Guide.
No. In many cases, agents can work with existing platforms through supported APIs, integrations, and workflow interfaces. The implementation approach depends on the current architecture, system capabilities, data access, and security requirements.
Agents should be designed to validate important information, check whether actions succeeded, and recognize when they cannot resolve a request reliably. Defined fallback procedures can route exceptions to human staff rather than allowing an uncertain or failed action to go unaddressed.
Timelines depend on the use case, data readiness, integration complexity, testing requirements, and governance approvals. A focused workflow with accessible data may be implemented more quickly than a multi-channel solution that requires extensive integrations and operational changes. A discovery assessment can help establish a realistic timeline.
