AI Deployment
From prototype to production. Built to last.
Most AI projects die between the demo and deployment. At Ingram, deployment isn't a phase — it's the discipline. We architect, build, and ship production AI systems that hold up under real traffic, real data, and real scrutiny. Because we're an R&D lab first, we solve the hard engineering problems before they reach your users.
The Deployment Lifecycle
We own the full path from validated prototype to a live, monitored production system — not just the proof of concept.
Architect for Production
We start where most projects fail: designing an architecture that survives contact with real users. Model selection, data flow, failure modes, latency budgets, and cost ceilings — decided deliberately, before a line of production code is written.
Build & Harden
We build the system and the scaffolding around it — evaluation harnesses, guardrails, fallbacks, and security controls. Every deployment is penetration-tested and designed with zero data retention by default.
Ship to Production
Weeks, not quarters. We deploy into your infrastructure or ours, with staged rollouts, load testing, and a clear path to scale. We've shipped AI systems for companies serving millions of users.
Monitor, Evaluate, Iterate
A deployment isn't done when it ships. We instrument every system with monitoring, drift detection, and performance analytics from day one — so quality is measured, not assumed.
What We Deploy
Custom AI systems engineered for your domain — not off-the-shelf tools bent to fit.
Custom AI Agents
Multi-agent architectures and autonomous workflows that take real actions in your systems — for customer support, operations, research, and internal tooling.
LLM-Powered Workflows
Retrieval, summarization, classification, and generation pipelines wired into your data and products — with evaluation and guardrails built in.
Custom & Fine-Tuned Models
When a general model isn't enough, we train, fine-tune, and deploy models built for your data, your constraints, and your performance targets.
Prototype-to-Production Rescue
Have a promising demo that won't scale? We take validated prototypes — including vibe-coded ones — and re-engineer them into systems you can trust in production.
Deployment, in Depth
The deployment problem looks different depending on what you're shipping. Here's how we approach each.
Deploy AI Agents
Custom AI agents that take real actions in your systems — scoped, hardened, and instrumented for production.
Learn more →Prototype to Production
Closing the gap between a working demo and a system you can trust — including vibe-coded prototypes.
Learn more →LLM Workflow Deployment
Retrieval, summarization, and generation pipelines deployed with evaluation and guardrails built in.
Learn more →How We Engage
A productized path that de-risks the decision before it gets expensive. No open-ended discovery, no surprises.
Deployment Architecture Review
A focused, fixed-scope engagement — typically around two weeks. We pressure-test your use case and produce a concrete deployment plan: architecture, model choices, risks, timeline, and cost. You keep the plan whether or not we build it together.
Build & Deploy
Fixed-scope milestones against the plan. We build, harden, and ship the system into production — penetration-tested, instrumented, and integrated with your stack. Weeks, not quarters.
Monitor & Iterate
An optional ongoing engagement: monitoring, drift detection, evaluation, and iteration as your usage and requirements evolve. Or a clean handover to your team — your call.
Engagements typically start with a free consultation to scope fit, followed by the paid Architecture Review. We'll be direct about cost and timeline before you commit.
Why Deploy With Ingram
A generic integrator wires together other people's tools. We're an R&D lab that deploys — so the engineering reflects actual frontier work.
Research-Grade Engineering
We publish original AI research, then build from it. Our clients get production systems informed by the hard problems we solve in the lab — not by tutorials.
Security-First by Default
Every deployment is penetration-tested. We've run live AI pentesting on fintech applications and apply those findings to everything we ship.
EU Compliance Depth
GDPR-native, with EU AI Act and ISO 42001 frameworks built into the deployment process — not bolted on afterwards.
Proven at Scale
We've deployed AI for Photoroom, Composio, Roopairs, and others — systems that serve millions of users and can't afford to break.
What You Own
Handing a production system to an outside team is a real risk. We structure engagements to remove it.
You own all code, models, and IP. Everything we build is yours — source code, weights, prompts, and infrastructure definitions.
Deployed in your infrastructure. Your cloud, your accounts, by default. No dependency on us to keep the system running.
The architecture plan is yours to keep. Even if you stop after the review, you walk away with a deployment plan you can act on.
Your data stays yours. Zero data retention by default. Your data never trains our models or anyone else's.
Penetration-tested before it ships. Every deployment is security-tested, with findings documented and handed over.
A clean handover, whenever you want it. Documentation and knowledge transfer so your team can run and extend the system without us.
Ready to Take Your AI to Production?
Tell us what you're building. We'll tell you what it takes to deploy it — reliably, securely, and at scale.