Product update: Build agents that onboarding teams trust

Integration teams, we need to talk about AI agents.

You've been asked to build them. You've seen the demos. You've watched developers spin up prototypes in LangChain and business units buy pre-built agents that promise instant automation.

But you know what they don't: getting to production is a different game entirely. It requires handling errors gracefully, managing tokens efficiently, enforcing governance, and ensuring 99,99% uptime. The same challenges you've been solving for years with integrations.

Today, we're excited to announce that Digibee—the platform already trusted to run 3 billion enterprise transactions monthly—now gives integration teams everything needed to build, test, and deploy production-ready AI agents.

Without learning a single line of Python. Without building out and onboarding to a complex, siloed AI stack.

28% accuracy gain in the first iteration.
As an early adopter, one of the world's top 20 banks increased accuracy from 62% to 90% by rebuilding an agent using Digibee.

The pressure is real (and growing)

The push for AI agents isn't slowing down. According to KPMG's latest research, 90% of organizations report board-level pressure to adopt AI—up from 68% just three months ago. IDC predicts a 10x increase in enterprise AI agent usage over the next five years.

But here's what's actually happening:

• Business units are buying vertical agents without understanding integration requirements.
• Shadow AI is spreading faster than shadow IT ever did.
• Development teams are building agents in isolation using complex SDKs.

The result? Agent sprawl.

Ungoverned agents accessing systems they shouldn't. Inconsistent implementations of business rules. Token costs spiraling out of control. The same chaos you've spent years eliminating from your integration landscape.

Why integration teams are perfectly positioned for agent success?

Here's what others don't understand: building reliable agents is 80% integration, 20% AI.

Think about what makes agents fail in production:

• Can't handle API errors gracefully (you've been handling errors for years)
• Consume too many tokens with raw data (you're experts at transformation and filtering)
• Violate business rules (you encode these rules daily in workflows)
• Lack governance and observability (you wouldn't dream of deploying without it)

Your integration expertise isn't just relevant to agent building, it's essential. It’s also what makes you the best expert to know when to build agents.

Before diving into capabilities, let's address a critical point: not everything should be an agent.

Using AI for deterministic processes is like 3D-printing a plastic spoon—impressive but impractical.

Digibee delivers a single platform for building:

• Agents
• Traditional integrations
• or—most powerfully— workflows that combine both

Let agents handle the variable, complex decisions while deterministic pipelines enforce the rules that can't be broken.

What's new: agent building designed for integration teams

The agent component: simple sophistication

With the agent component, we've embedded agent-building expertise directly into the platform. Connect to any LLM through one interface, no need to learn each model's quirks.

When you remove the learning curve, teams are incentivized, not penalized, for choosing the best model for any given task. As you write prompts, you get real-time guidance on how to optimize based on each model's best practices.

Critically, you can set constraints where you want them. Model allow/deny lists ensure teams are only using approved models, helping you standardize model preferences and control costs across teams.

Another feature integration teams will love? Agents built with Digibee can ingest your existing unstructured files and domain-specific context and then format outputs for even the pickiest downstream systems. Your existing integration patterns become agent capabilities.

Custom MCP tools: easy as pie(pelines)

Less than a year old, MCP (Model Context Protocol) tools are the accepted standard for getting agents to take predictable, controlled action.

With Digibee, any workflow you've built can be exposed as an MCP tool that’s reusable, composable, and accessible to agents.

This changes everything.

That complex Salesforce-to-SAP integration you built? It's now a tool agents can use.

The data validation pipeline that took weeks to perfect? Agents can leverage it instantly.

Your business rules, encoded in workflows, become guardrails agents can't violate. Even better: these tools work with any agent—ones you build in Digibee or third-party agents you purchase.

Integrated evaluations: prove performance

Unlike traditional integrations that run against static specs, agents require more subjective evaluation. With Digibee, you create experiments, test agent performance, and track accuracy—all within the platform.

When new scenarios emerge in production, replay them in development as additional experiments, iterate and improve.

Runtime protection: enterprise-scale security

Agent security can’t be an afterthought. Digibee guardrails provide runtime protection to detect and prevent data leakage like PII or secrets. Access controls keep agents from reaching for tools they don’t need (or shouldn’t have), preventing them from taking unauthorized action with your data or applications.

Beyond these specific controls, every agent benefits from enterprise security built into the Digibee platform. Each agent:

• Executes in isolation within its own Kubernetes Pod
• Communicates only with approved endpoints through Zero Trust Network Access
• Encrypts all data in transit (TLS 1.2) and at rest (AES)
• Maintains full audit trails of runtime activity

Together, these layered controls ensure agents can run autonomously without compromising data integrity or organizational security.

Integrated observability: keep accuracy strong

Every agent interaction is traced and logged. You’re able to inspect production performance, identify bottlenecks, and reproduce failures safely in development. It’s simple, really: Digibee understands the observability standards you demand from integrations and applies them to agents.

With Digibee, you have everything you need to build agents. Integration engineers don’t need to be come Python experts. You don’t have to invest in and stitch together a complex AI stack. And you don’t need to grapple with solutions that haven’t figured out enterprise scale or security. Instead:

• Work in one proven platform for both your agents and traditional integrations, going from agent-curious to confident with ease.
• Build agents fast with reusable MCP tools that give agents what they need to get the job done—without going rogue.
• Use guardrails, governance, and production monitoring to confidently run agents in production.  

The enterprises that win won't be those with a tangle of vertical agents or those who are reliant on siloed AI teams. The winners will recognize integration teams already have cross-enterprise context and integration expertise—80% of what's needed for agent success. They’ll equip these teams with a unified platform that bridges the remaining 20%.

Ready to add agent building to your integration expertise?

In our humble opinion, we’re confident the answer is yes. Schedule a demo to see agent building in Digibee today.