Veteran data science for enterprise AI.
We find the use case worth doing, prove it on your data, then build and run it. We don't resell the hardware, cloud or licenses we recommend.
- Use-case discovery and ranking
- Prototype on your data; go / no-go
- Production engineering and MLOps
- Run, govern and improve
Who delivers the work
- avg experience per person
- 15+ years
- publications
- 39
- citations
- 837
- in research funding led
- $5.8M+
- Careers built at
- Microsoft
- Meta
- X/Twitter
- Lyft
- Goldman Sachs
- U.S. Department of Energy
- Carnegie Mellon SEI
- Pittsburgh Supercomputing Center
- IBM Quantum Network
- Degrees and affiliations
- Carnegie Mellon
- Stanford
- UC Berkeley
- Harvard
- NYU
- NSF Postdoctoral Fellowship
- DARPA
Figures cover two of our VPs and the ten consultants who work with us.
Why clients bring us in
Data scientists, researchers and engineers who ship
Meet the teamVeteran talent with published research behind them, forward-deployed into your team.
One team, discovery to production
How we engageThe same veteran data scientists, researchers and engineers staff every stage.
Numbers with their limits
Token Economics SprintWe help you find the use case worth doing. Live engagement models: interactive ROI and scenario dashboards, built per engagement.
Delivered with your partners
For partnersPartners bring our data science engagements to their customers, and work runs on infrastructure you have already invested in.
The BridgeTek Method
Every engagement follows the same three steps, from many AI ideas to one proven use case to a system running in production. The same veteran team carries the work through all three. Join at the step your work has reached.
Discover
Find the use case worth doing. Veteran data scientists, researchers and engineers interview the people who own the problem, rank the ideas by value, and model the compute cost before capacity is ordered.
Prove
Show it works on your data before real budget is committed: a working prototype, a tested ROI hypothesis and a clear go / no-go, built so the work carries forward into production.
Deliver
Build it, run it and plan the next one: a governed production system, monthly optimization and governance, and veteran practitioners embedded in your team where the work calls for it.
Your pilot list is too long
Every department has an AI idea. Budgets end up spread across a handful of pilots that never impact the business. Four stages with one veteran team allow you to execute the right use case. Each one sits under a step of the BridgeTek Method. Start at the stage where your problem actually is.
AI Discovery Sprint
Discover. Stakeholder interviews with veteran data scientists, researchers and engineers that surface where AI creates real value and turn it into a ranked, owned starting point, with a recommended Proof-of-Value.
Start here if:
You know AI matters and can't get internal alignment on where to point it, or a prior attempt stalled.
Proof-of-Value
Prove. A working prototype against real data, a tested ROI hypothesis and a clear go / no-go before real budget is committed, with a sizing of the compute it would run on.
Start here if:
A use case has an owner and no evidence, and a funding decision is stalled on it.
Execution Pod
Deliver. Data governance, process architecture, engineering and MLOps that take a validated go decision to a governed, production-grade system.
Start here if:
The Proof-of-Value came back "go" and the team isn't in place to build it.
Managed AI Services
Deliver. Monthly optimization, governance, and a standing backlog of the next use cases worth funding.
Start here if:
A system just went into production, or nobody's watching the quality or what it costs to run.
Don't know where to start?
Token Economics Sprint
About the sprintTake stock of existing or projected use cases before capacity is ordered. Models metered, rented and owned inference cost, shows the volume at which the cheapest option changes, and hands the model over.
Forward-deployed data scientists
About forward-deployedVeteran data scientists, AI engineers and researchers embedded in your team, for work where a packaged engagement is the wrong shape.
Where partners plug in
Partners can bring our data science engagements directly to their customers. Software vendors whose platforms sit in the deployment stack can co-sell and co-deliver them. How partners work with us →
Infrastructure our clients already run
We support AI workloads on any infrastructure our clients have already invested in, we don't require them to buy any particular stack.
Proof-led production outcomes
A sample of what this team has shipped. See all their work →
Financial services
Agentic compliance automation: a multi-agent system automating a fraud and sanctions investigation workflow for a large financial institution.
Energy & utilities
Bottom-up ML forecasting pipeline for a state grid-electrification study, findings submitted to the California Public Utilities Commission.
Trust & safety
7.5 years building ML detection systems for spam and coordinated inauthentic behavior at X/Twitter, then cross-platform at Meta.
GPU infrastructure
GPU cloud observability platform built end to end (scheduler, GPU and node health, fabric, storage, tracing unified into one multi-tenant platform) on production infrastructure already carrying customers, off a legacy monitoring stack. First production release in 2 weeks against a hard external deadline, with no window in which the fleet went unseen.
Shipped work by the team, before and since BridgeTek.
What a client said about a recent GPU observability build
“We pointed them at some of our hardest problems, and they consistently strategized, self-directed, engaged stakeholders, and executed complex software deliverables at scale. … Early on, we put them in charge of building our observability and monitoring layer to address one of our core problems: SLA enforcement. The work their "full stack data scientists" delivered was excellent! It directly enabled us to secure an exclusive partnership with an industry giant …
They let us focus on our core business while delivering provable short-term wins that justified continued investment in their work. … Would highly recommend!”
On work delivered by Transmute Data, whose consultants deliver BridgeTek's data science engagements. Used with the endorser's written permission; client name withheld.
BridgeTek Labs
A dedicated home for our data science and AI engineering research, benchmarks, experiments and technical findings.
What we've built to run this
Internal tooling: the reason delivery moves fast, available for licensing.
Scout
The account-intelligence engine behind every stage. It reconciles account data, stakeholder input and shifting priorities so the team stays oriented toward maximum business value every step of the way.
Live engagement models
Interactive ROI and scenario dashboards built per engagement, so a business case can be stress-tested in the room.
Start with a conversation
A consultation with the team about where your AI work is stuck.