Agentic AI in production — governed, observable, and inside your own estate.
We bring the accelerators, the inference platform and the engineers that take AI from proof of concept to a running part of your business workflows.
Operating model
A low-code platform for building scalable agentic workflows and deploying them as APIs — without having to solve governance, security and end-to-end observability yourself.
- Compose agents and workflows visually, ship them as governed APIs
- Policy, access control and audit trails built into the runtime
- Traces, evaluations and cost visibility across every call
- We integrate it into your business with you — and we are open to giving the IP to the business using it
Open model hosting
A scalable inference engine for open models, run on premise. It carries millions of LLM calls with guardrails and GPU scheduling in the platform itself.
- Chat completion, embedding, re-ranking, OCR and small language models
- Scales to millions of inference calls
- Built-in guardrails on inputs and outputs
- GPU scheduling and capacity management across teams
Forward deployed engineers
Our expert engineers work inside your team to augment its capability and make sure adoption happens quickly and in the right way — and they stay for the journey.
- Sit with your engineers and domain owners, not beside them
- Build the first workflows end to end, then the next ones alongside you
- Stay embedded as the platform grows, not just for the first delivery
Why we run it on your premises
For banking, healthcare and government workloads, where the model runs is part of the architecture — not a deployment detail settled later.
Data stays in your estate
Prompts, documents and embeddings never leave the network you control.
Evidence for your regulator
Model lineage, guardrail decisions and full call traces are available for audit.
Predictable cost at volume
Inference runs against capacity you already own, scheduled across teams.
Open models, your choice
Swap or upgrade models without rewriting the workflows built on top of them.
From first workflow to production
One engagement, four stages. Each one ends with something running, not a document.
Discovery
We map the workflows worth automating and agree what good looks like.
Pilot
A real workflow built on BadgerFlow against your data, with your team.
Integration
Platform and inference stood up in your environment, wired to your systems.
Scale
Our engineers stay on as the estate grows. Where it makes sense, the IP sits with your business.
Start with one workflow.
A discovery call takes an hour. We look at where AI would actually change your operations, and what it would take to run it inside your estate.