Forward Deployed Engineering by Schub
Your agents, in production.
Secure from day one.
A managed team that works inside your company to design, ship and run agent systems end to end.
The forward deployed model, without the vendor lock-in
Forward deployed engineers work alongside a business and stay until the solution works in production. But when they work for a platform vendor, their job is to get you to adopt that platform.
But at Schub, we work for your outcomes, not for a vendor.
We pick the models, gateways, clouds and tools that fit your problem, and switch them when something better comes along.
We’ve already helped AI-native companies build to support enterprise demands. Now we bring that experience to your startup.
Your Schub Pod
Sized to your stage
Forward Deployed Lead
Owns the outcome and finds the next problem worth solving.
Agent & Integration Engineers
Build agents and connect them to your systems and data.
vCISO & Cloud Security Architect
Identity, permissions, data governance and SOC 2.
Delivery Lead
Roadmap, priorities and reporting.
Our Agents
Schub's own agents work as your first line of defense: observability, triage and routine tasks handled end to end.
Forward Deployed Engineering
Who it's for
AI-native startups with enterprise or regulated customers, that trust agents to multiply what their team can do.
- Your product or operations depend on LLMs, or soon will.
- Your customers ask for SOC 2, data policies and audit trails before they sign.
- You want cloud and inference spend you can predict.
Forward Deployed Engineering
How we work
- A managed team, never a headcount. We staff the work; your Forward Deployed Lead stays with you.
- We join at any stage: an idea to prove, a product to harden or a platform to operate and certify.
- We report outcomes, not hours: what shipped, what it changed and what comes next.
How an engagement starts
01
Understand the problem
A call to map your process, data, systems and risks before we talk tools.
02
Deploy the pod
A team sized to your tier, embedded with your product and engineering people.
03
Run and evolve
We operate what we ship and move on to the next use case.
Three ways to engage
Same model, different scope and pace.
Every tier is a recurring managed service. What changes is capacity, speed and how much security and compliance is included. Start small and move up when the results justify it.
Launch
Prove the first use case
- Proof of concept or one focused component
- Shared Forward Deployed Lead
- Flexible engineering dedication
- Security and compliance (from Build)
Review cadence: monthly
Build
Run agents in production
- Full pod, including vCISO and Delivery Lead
- Agent platform, LLM gateways and observability
- Several initiatives in parallel
- Security baseline and path to SOC 2
- Our agents watching your stack
Review cadence: every two weeks
Scale
Make AI a core capability
- More throughput, faster time to production
- 24/7 support
- Security and compliance certifications
- Continuous governance and cost control
Review cadence: weekly
Every pod is sized to the problem, so we recommend a tier on the first call.
What we run in production today
Facts, not claims.
Shipping one agent is easy. Keeping a fleet available, observable, affordable and ready for a security review is where teams get stuck.It's the work our teams do every week.
Reliability
Better uptime
Resilient infrastructure, fallback across model providers and fast incident response.
Cost
Cloud cost optimization
Right-sized infrastructure, so more usage doesn’t automatically mean higher costs.
Observability
Token observability for inference
Track token usage, latency, and cost by agent, model, and customer.
Operations
Agent fleets in production
Gateways, routing, permissions and evals across many agents, with a record of what each one did.