Ways to work with us.

Whether you need a system built, legacy code modernized, or a direction set, we bring the same flocking discipline to AI in SAP.

Service

SAP Joule agent development

Custom SAP Joule agents - built in Joule Studio and as A2A-native agents on BTP, grounded in your data, observable from day one, and ready to grow into the SAP standard.

open →
Service

AI agent development

We design, build and ship multi-agent systems for SAP - from a single well-scoped agent to an orchestrated flock, wired to your data via A2A and MCP.

open →
Service

AI-in-SAP advisory

Strategy, architecture and guardrails for teams adopting AI inside SAP. Where agents help, where they don’t, and how to keep them observable and safe.

open →
Service

AI product development & consulting

From a first use case to a shipped, measurable product. We take AI ideas through discovery, build and launch - and stay honest about what belongs in production.

open →
Service

Custom ABAP modernization with AI

Read, refactor and document legacy ABAP faster with AI in the loop - untangling old code into something your team can safely maintain and extend.

open →
Service

MCP server development

Expose your SAP data and actions to agents over the open Model Context Protocol - clean, governed tool interfaces instead of brittle one-off integrations.

open →
Service

Agentic AI implementation

End-to-end delivery of agentic systems - orchestrated flocks of bounded agents wired into S/4HANA, BTP and Joule, observable and scored from day one.

open →
Service

Vibe-coding prototype in days

Want to see the idea working this week? We jump in and vibe-code a quick, hands-on prototype in days - then, once it proves its worth, move it to a real implementation with the security and architecture it deserves. Tell us the idea; we’ll build it fast.

open →

How we deliver

From use case to production.

A research-backed AI lifecycle - analysis first, a fast prototype, honest evaluation, then a production-grade build you can trust and keep improving - instrumented end to end with Boidra Platform.

  1. 01
    Discover
  2. 02
    Prototype
  3. 03
    Evaluate
  4. 04
    Deploy
  5. 05
    Operate
Boidra Platform · spans → scores → trends
Traced from the first prototype, scored through production
AI delivery lifecycle: Discover, Prototype, Evaluate, Deploy, Operate. Boidra Platform instruments the Prototype, Evaluate, Deploy and Operate phases.
01Discover

Use-case analysis

We start with the problem, not the model - mapping the use case, the data you have, and whether AI is even the right tool. A short discovery sprint before a line of production code.

Workshops · feasibility · baseline metrics

02Prototype

Vibe-code a working prototype

A hands-on prototype in days, not quarters - so you see the idea working before committing. We build fast with modern AI tooling.

Claude Code · GitHub Copilot CLI · GitHub

03Evaluate

Evaluate & guardrail

Explicit eval criteria set before coding: output quality on your inputs, latency, cost. We build datasets from real traces in Boidra Platform and run LLM-as-judge scoring against them, with prompts versioned as first-class assets and guardrails on every input and output.

Boidra Platform · eval sets · LLM-as-judge

04Deploy

Ship to production

Real implementation with the security and architecture it deserves - CI/CD quality gates, on SAP BTP and your landscape, wired over A2A and MCP so nothing is locked in.

BTP · CI/CD gates · A2A · MCP

05Operate

Observe & improve

Every agent step emits a span into Boidra Platform, scored in production. We monitor quality, hallucinations, latency and cost - and act on the outliers, so the system keeps getting better.

Boidra Platform · scoring · monitoring

We use our own product

Built and tested with Boidra Platform

The agents we ship for you are developed and tested on Boidra Platform, our own agent-observability product. From the first prototype, every agent turn, LLM call and tool step is a traced span - so we can score behaviour, build eval datasets from real runs, and catch regressions before they reach production, then keep watching once they do.

  • PrototypeTrace every run from day one
  • EvaluateLLM-as-judge scoring on real traces
  • DeployRegression checks before go-live
  • OperateLive scoring for quality, latency & cost

Have a use case in mind?

Tell us what you’re trying to automate in SAP. We’ll tell you - honestly - whether an agent is the right tool, and how we’d start.

Give us a use case →