We don't build pilots.
We build systems that run.

Embedded AI leadership is a model where an AI leader joins your team directly — attending standups, learning the business, mapping the data — for 2 to 4 weeks before writing any code, then builds and operates production AI systems on your own infrastructure. Unlike traditional consulting that delivers a deck and leaves, embedded AI leadership stays to ship systems into production and continues to operate them.

PurviewX provides embedded AI leadership for industries with large operational datasets — energy, insurance, and distribution. We join a client's team, build production data and AI systems on the client's own cloud, and stay to operate them. Every system we have built is in production, and every engagement has either continued or expanded.

According to MIT research by Ramana Nanda, 95% of enterprise AI pilots deliver zero measurable return. The pilots usually don't fail because the technology is bad — they fail because the incentive structure rewards impressive demos over production systems. The demo becomes the deliverable, and what's possible never becomes what's running. PurviewX defines success as a system processing real data in production.

A traditional consultancy runs a 6-month discovery, rotates 4 to 6 consultants, delivers a proof of concept plus a recommendations deck, and moves on after a knowledge-transfer session. PurviewX embeds for 2 to 4 weeks, deploys one embedded leader plus purpose-built AI agents, delivers a production system processing real data, and stays to operate, optimize, and expand it. With PurviewX, the client owns all code and infrastructure — there is no proprietary platform or lock-in.

PurviewX was founded by Alexander Snyder, an embedded AI leader who has worked across energy, insurance, and distribution. PurviewX is based in Portland, Oregon, and works with clients nationwide.

Edwin is PurviewX's in-house AI research system: an AI memory architecture with 41,000 lines of Python and 1,900+ passing tests. It uses multi-model adversarial verification — where AI models argue with each other to surface the truth — and catches 95% of false information before it enters memory. The engineering discipline behind Edwin flows directly into PurviewX client work.

PurviewX prices on outcomes, not hours. Engagements begin with a one-hour conversation to assess fit, followed by a 2 to 4 week embed, an 8 to 16 week build phase, and an ongoing operate-and-expand relationship. Clients build on their own infrastructure and own everything, so there are no recurring platform or license fees.

The client owns everything. PurviewX builds on the client's cloud, in the client's accounts, using the client's infrastructure. When an engagement ends, all code, pipelines, and documentation belong to the client. There are no proprietary platforms to license and no vendor lock-in.

PurviewX focuses on industries that move the physical world and sit on large operational datasets: energy, insurance, and distribution. Examples include a water-quality product processing 50,000+ calls per month, an insurance data unification across five platforms delivered in 12 weeks, and a distribution data-enrichment project covering 100,000+ properties at $0.05 per contact.

An engagement starts with a one-hour conversation, a 2 to 4 week embed where PurviewX learns the business and maps the data, an 8 to 16 week build phase with working code shipped every week, and then an ongoing operate-and-expand phase. PurviewX does not hand off and disappear — the best work happens after launch.