If you talk to operational leaders today, you hear a familiar pattern.
They’ve automated tasks, built workflows, and connected systems. They’ve rolled out RPA bots and experimented with AI copilots. And still, when a customer changes an order, a supplier sends the wrong reference, or a partner asks for an urgent update, someone goes back to Outlook.

Work slows the moment it leaves a structured system and lands in a shared inbox. People become the glue between tools: forwarding emails, searching for IDs, chasing details, stitching together context. It’s not that automation has failed. Rather, it’s that it stopped at the point where real work begins.

Analysts call this the automation plateau. We call it the biggest opportunity in enterprise AI.

And it’s exactly why Agentic Process Automation (APA) exists.

The automation plateau: where traditional tools lose their power

Over the past decade, enterprises have made impressive progress in automating tasks: faster data entry, more consistent workflows, cleaner integrations. Yet, despite billions in investment, most organizations still describe the same reality: work moves slower than expected, exceptions consume more time than standard cases, and people are the glue holding processes together. Every time a process crosses a system boundary, automation stops and human middleware takes over.

Gartner’s latest Magic Quadrant for Business Orchestration and Automation Technologies (2025) captures this tension clearly:

“Organizations that focus only on task-level automation hit a wall of complexity when attempting to scale; orchestration and adaptive intelligence are now the key differentiators in enterprise automation maturity.”

RPA performs well when every step is predictable. Workflow tools handle the “happy path” but struggle with exceptions. Integration platforms pass data along, but don’t understand the content. Even AI copilots, useful as they are, assist humans. They don’t coordinate work.

Meanwhile, inboxes remain the operational front door.
It’s where orders arrive, complaints escalate, approvals stall, and relationships are maintained. It’s also where context is buried, and where automation has historically stopped.

APA moves automation from the application layer to the actual flow of work.

So, what is Agentic Process Automation?

Agentic Process Automation is automation that thinks before it acts. 

Instead of blindly following predefined rules, AI agents interpret each situation, decide what should happen next, and carry out actions across systems with context and precision. 

This approach blends three core capabilities. Firstly, Process Intelligence, which reveals how work truly moves across teams, inboxes, tools, and exceptions. Often very differently from how processes were designed on paper. Secondly, custom-trained LLMs that understand an organisation’s real vocabulary, rules, priorities, customer profiles, and product structures rather than relying on generic internet knowledge. And third, Agentic Orchestration, a governed layer of autonomous agents that respond to signals, plan next steps, update systems, notify people, or escalate when human judgment is needed. 

Together, these elements transform unstructured, unpredictable requests into smooth, end-to-end workflows that continuously improve over time. It’s automation built for how work actually happens, not how ideal state diagrams imagine it.

From Process Intelligence to actual process understanding

Every meaningful process starts with a message: a change request, a shipment update, a complaint, a deadline, an invoice issue. These messages rarely arrive neatly structured. They show up as forwarded threads, vague subject lines, screenshots, or partially filled PDFs.

Tekst begins by analysing these conversations at their source.
Instead of starting from system logs, we start from the inbox, because that’s where intent is clearest and where friction hides. This approach, which we explored in depth in our article Why Process Intelligence Needs to Start in the Inbox, gives organisations a view of their real processes, not the theoretical ones.

Once work becomes visible, improving it becomes far simpler.
And once the system understands how work flows, agentic automation can take over the parts that slow teams down, with accuracy and context.

Where intelligence becomes action: the APA layer

Real-world work isn’t linear. Cases change direction. Priorities shift. People ask follow-up questions. Systems disagree. Standard flows break.

This is what APA is built for.

Picture an email about a delayed delivery. An APA agent can understand the message, extract the order ID, check its status in SAP, update the CRM ticket, send a clear, correct reply and surface anomalies to a human when something doesn’t add up.

All of that in seconds, without anyone manually combining information across systems.

Humans are still in control, but in a different role. Instead of performing every step, they supervise boundaries, teach new patterns, approve sensitive actions, and guide exceptions. The organisation shifts from doing the work to designing how work should flow.

It’s a safer, more scalable bridge between manual work and autonomy. One where governance is built in by design.

APA vs every tool you already know

It helps to place APA within the landscape of automation tools.

RPA automates predictable, stable tasks inside individual systems; APA automates contextual decisions across systems. Process Intelligence reveals where bottlenecks live; APA addresses them immediately. EDI and integration platforms move data; APA understands meaning, even when the input is messy, incomplete, or inconsistent. RPA made tasks efficient; APA makes operations intelligent.

The path toward the Self-Improving Company

When APA and Process Intelligence reinforce each other, something important happens: processes evolve continuously.

An APA agent that sees repeated confusion around a surcharge can surface the root cause. If a workflow repeatedly stalls with one team, the system highlights it. If a certain approval always causes delays, APA doesn’t just route it better, it also reveals why.

Work doesn’t just get done faster; it gets redesigned in real time.

This is the foundation of a Self-Improving Company — an organisation where every interaction makes the next one smarter.

Why APA is gaining momentum now

Several forces converge to make APA not just possible, but necessary. 

Firstly, foundation models have matured to the point where they can be securely customised for domains like medtech, logistics, manufacturing, and services. Secondly, enterprise systems are now API-first, allowing agents to safely perform actions across tools. Lastly, leadership teams expect real, measurable AI outcomes, not pilots or prototypes.

APA fits this moment: practical, governed, high-impact, and immediately measurable.

Tekst’s approach to Agentic Process Automation

Tekst is built for enterprises where the inbox drives operations, especially in industries like medtech, manufacturing, logistics, and services.

Our platform brings together 3 layers of capability:

Integrations
Connecting inboxes seamlessly with systems like SAP, Salesforce, Dynamics, Zendesk and industry-specific tools. For example:

• Accounts payable automations
  
  
• Email to Case
  
  
• Shared inbox management
  

Custom LLMs
Models tuned to understand the nuances of your organisation: its terminology, workflows, customer base, products, and risk patterns.

Agentic Workflows
Governed AI agents that understand context, take actions, handle exceptions, and improve over time.

This combination helps organisations move from scattered, manual inbox-driven work to a consistent, intelligent operational layer that gets smarter with every cycle.

For real examples across sectors, explore our customer stories.

Where to begin with APA

You don’t need to transform your entire organisation at once.
The best starting point is simple: look at the inboxes that trigger the most downstream work such as orders, incidents, approvals, complaints, vendor correspondence.

These inboxes hide your biggest automation opportunities. They also deliver the quickest ROI.

From there, connect agents to your operational systems, introduce case interpretation and enrichment, and gradually expand automation to more workflows. Within weeks, the impact becomes visible. Not just in efficiency, but in clarity and control.

Automation used to mean efficiency. Now it means evolution.

RPA automated the obvious. APA automates the overlooked.

It closes the gap between how your processes are designed and how they actually run,  turning unstructured chaos into structured, intelligent, self-improving work.

If you want to explore what Agentic Process Automation could mean for your organisation, we’re here to help.

👉 Talk to Tekst and see APA in action.

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FAQ

_{1. What is Agentic Process Automation (APA)?}

Agentic Process Automation (APA) is a new form of enterprise automation where AI agents can understand incoming work, make decisions, and take actions across systems. Unlike RPA, which follows fixed rules, APA uses reasoning, Process Intelligence, and custom-trained LLMs to automate complex, context-heavy workflows, especially those originating in shared inboxes.

_{2. How is APA different from RPA or traditional workflow automation?}

RPA automates predictable tasks inside individual systems. APA automates the decision-making across systems. Where RPA breaks when a process changes or an exception appears, APA adapts, interprets intent, and executes the next best action. It’s built for unstructured work, not just structured steps.

_{3. Why is Agentic Process Automation important for enterprises?}

Most enterprise work originates in inboxes: orders, complaints, approvals, vendor queries, changes, exceptions. APA turns this unstructured, high-friction work into automated, end-to-end flows. The result is faster response times, fewer errors, better visibility, and operations that genuinely improve over time.

_{4. How does APA work in a real business process?}

A typical APA workflow starts when an email or document arrives.
The agent interprets the message, extracts relevant data, checks other systems (ERP, CRM, ITSM), updates records, triggers workflows, sends responses, or flags inconsistencies, all autonomously. Humans intervene only when the AI agent hits a new or sensitive scenario.

_{5. What types of workflows benefit most from APA?}

APA is ideal for processes that start in a shared inbox or require cross-system actions. Common examples include:

• order changes and confirmations
  
  
• delivery updates and logistics issues
  
  
• complaint handling and customer service
  
  
• invoice exceptions and accounts payable
  
  
• vendor communication and procurement
  
  
• product incident reporting

These workflows tend to be unstructured, repetitive, and critical — making them perfect APA candidates.

_{6. Is APA safe for sensitive or regulated industries?}

Yes. APA operates under strict governance and human oversight. Tekst’s implementation includes audit trails, escalation rules, approval layers, and domain-specific LLMs that keep data within secure environments. It is used by industries such as healthcare, manufacturing, medtech, and logistics where compliance is essential.

_{7. How does Process Intelligence support APA?}

Process Intelligence provides visibility into how work actually moves through inboxes and systems. APA uses these insights to automate decisions, detect inefficiencies, and improve over time. The combination creates a self-improving operational layer.

_{8. Do humans stay in control with APA?}

Absolutely. APA changes the role of humans, not their importance. Humans define the guardrails, approve sensitive cases, teach new scenarios, and oversee exceptions. APA handles the repetitive coordination work so people can focus on higher-value decisions.

_{9. How long does it take to see value from APA?}

Most organisations see measurable improvements within weeks, especially when starting with a shared inbox or a high-volume workflow. APA doesn’t require system replacements; it plugs into your existing ERP, CRM, and email environment.

_{10. What is the connection between APA and Shared Inbox Management?}

Shared inboxes contain the signals that start most operational processes. APA transforms inbox messages into structured, automated workflows by interpreting intent, assigning ownership, and executing actions. It is the natural evolution of Shared Inbox Management into enterprise-wide intelligent operations.

_{11. Is Tekst an Agentforce alternative for agentic automation?}

Yes. Tekst offers a modern, flexible alternative to Agentforce by focusing on actionable Process Intelligence, robust inbox understanding, and fully governed agentic workflows. It integrates with existing enterprise systems without platform lock-in or heavy development.

_{12. How can my organisation get started with Agentic Process Automation?}

Start with one inbox or workflow that generates significant downstream work — such as order intake, complaints, or AP exceptions. Map the real flow using Process Intelligence, deploy agentic actions where they reduce friction, and scale from there. Tekst guides customers through this journey with proven frameworks and domain-specific models.