A delivery engagement that takes one prioritized business case and builds it into production AI, using the lean, user-centered Labs practices our team grew up on, adapted for ML and AI, and captured into a context layer that makes every future build faster.
The Primer tells you what to build. AI Assembly takes the top thin slice, stands up a balanced team alongside yours, and gets it live fast. Then we iterate on the real system. Reaching production early is the point: it turns opinion into evidence and starts returning value while we refine.
Leaders with a prioritized opportunity who want it built and in production, whether their team takes ownership or they want us to run it, not handed off as a slide deck.
Straight after an AI Primer, or any time you have a validated, high-value use case and need a team that can take it from concept to production with confidence.
Through the whole stack - just enough data, model and application to reach production.
Day Two operations and evals are in place from the first release, not bolted on later.
Scoped so it returns value early and sets up the next slice to go faster.
One principle guides the work: we build AI that delivers measurable business value, scoped as a thin slice that reaches production fast and improves through iteration. We avoid building AI for AI's sake.
Most of our method is not new. It comes from Pivotal Labs, the go-to engineering partner for venture-backed startups, building software with companies like Twitter, Uber, Salesforce and Google. When Pivotal was folded into VMware, Strongly's founders left to take its practices where the hardest problems had moved: AI and ML.
Every framing and modeling exercise is captured into an ontology, so the next slice starts further ahead.
Behavior validated with evals, model strategy and data grounding as first-class decisions, MLOps in the definition of done.
Pairing and knowledge transfer are optional. We can build the slice and operate it for you in production.
Discovery & framing workshops that feed the build
As we run discovery, model the domain and make decisions, we map the findings into a persistent ontology: your entities, systems, data sources, terminology and the decisions behind them. This is what separates AI Assembly from a one-off project.
Domain, data, systems and decisions, mapped as you build.
Agents and teams start each slice with real context, not guesswork.
Each build is faster and cheaper than the last.
AI Assembly runs the complete Labs flow for one use case, from framing through to a system running in production.
A model in production is the start, not the finish. AI Assembly plans Day Two from the start, so the slice keeps delivering value after go-live.
Monitoring, observability and alerting on the live system - dashboards, latency and uptime, incident alerting.
Evals in CI, with drift and quality checks on every change, and human-in-the-loop review.
Model routing by cost and task, caching to cut repeat calls, and spend dashboards and budgets.
We pair with your engineers, hand over runbooks and the Day Two playbook, and your team owns and runs the slice from go-live.
We run and maintain the slice as a managed service, so you get the outcome without standing up a team. Covered in depth by AI Day Two.
A working AI use case in production, the assets to operate it, and a context layer that makes the next build faster. Everything is yours to keep.
The thin slice live in your environment and serving real value.
Behavior validated and protected, running in CI.
Your domain, data and decisions mapped for reuse by future builds and agents.
CI/CD for the slice and the models behind it.
Dashboards, alerts and the Day Two playbook to run it.
Engineers and analysts who can extend and operate it, or we run it for you.
6 to 12 weeks to live and serving, operable on day one, with context captured so the next build is faster.
AI Assembly does not end with a handoff. We bring the people, the process and the platform to take a use case into production and keep it running.
Forward deployed engineers build the slice, from discovery through production.
The Labs practices we grew up on, applied to thin slices that reach production fast.
Workflows, AI apps and MLOps to take a slice to production and keep it running.
Scope an AI Assembly and turn a prioritized business problem into a live, production solution - built with you, or run for you.
or email sales@strongly.ai