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About Boxcar

Built by people who’ve shipped software for decades.

Leadership with over 75 years of combined software experience, advisors with deeper benches in the rooms that matter, and real machine-learning, data-science, and AI customer delivery since 2016.

Founders

Meet the leadership team.

Anthony Miller

  • Industry experience16+ years
  • Top strengthHuman-experience strategy
  • MissionEntrepreneur and human-centric technology strategist for over 16 years, helping ambitious companies sharpen their GTM, design, and AI strategy. Believes the most important job for AI isn’t replacing what makes us human - it’s protecting it, so the experiences and knowledge that matter most can be carried to the generations that follow. Home is Ithaca, NY, where he lives with his wife and two kids, coaches his daughter’s basketball team, boxes, and shows up for the community.

Praveen Raghavan

  • Industry experience20+ years
  • Top strengthBridging strategy and execution
  • MissionHelping organizations navigate disruption - through enterprise-wide transformation, technology-enabled change, and M&A-driven reinvention. A trusted CxO advisor across the U.S., Europe, and Asia, with delivery records spanning Telecom, Industrial Manufacturing, and Professional Services. Thrives at the intersection of strategy, technology, and people - helping organizations move faster, think bigger, and deliver measurable impact.

Justin Williams

  • Industry experience25+ years
  • Top strengthAI and software craft
  • MissionA career arc that started in Motorola assembly for embedded / IoT work, moved through DevOps and platform engineering, into data science, and — since 2016 — into applied AI, including patented IP. Believes we’re all pioneers in the AI transition, and what we pay attention to matters in shaping the future. A craftsman at heart, hoping for a future that’s collaborative, not isolating — technology with heart.
Advisors

Thought leadership and strategic reach.

Coming soon

The advisor bench is being assembled.

Detailed profiles will appear here as we close commitments. If you’re a senior operator, technologist, or strategist interested in joining as an advisor, get in touch.

Why we built this

Software development is hard. Achieving qauality agentive AI only raises the bar.

Every team building software now carries two responsibilities at once: understanding the craft of software and understanding the AI that ships inside it. That’s a lot to ask of any organization - especially while the underlying models keep changing under everyone’s feet.

We levered our hard earned experience in the challenging field of software to build Boxcar to roll those lessons up into one platform. A way for teams to make the leap to consistent, measurable, evidence-based success - without having to acquire the bruises themselves.

60+ Years combined software experience
2016 Shipping ML / AI to real customers since
4 Industries pressure-tested in production
Anthropic GCP · Gemini OpenAI Azure AWS Fireworks Tinman Kinetics M7
Pencil-on-graph-paper sketches: progress indicators, launch-vs-landing time charts, dependency progress bars, and design notes for an autonomous mission-control concept.
Concept
A live operations dashboard with a globe live-satellite view, data status tracker, machine-vision cameras, fuel-cells heat map, alerts panel listing pressure and ingress events, and a launch-window timeline.
Operating system
Solution Spotlight Aphelion Aerospace · NASA SBIR

Autonomy that isn’t isolation - even at thirty minutes one-way.

Aphelion Aerospace and Boxcar built a fully autonomous, real-time AI for launch operations in environments where humans have to stay in the loop but can’t possibly be in the moment - environments like a Mars launch, where one round trip of communication is roughly thirty minutes. Differentiable deep learning and agentive models on the edge with the vehicle, paired with terrestrial cloud compute for what doesn’t have to ship. The result enabled mission profiles that simply couldn’t be designed before - and proved that fully autonomous systems can still be part of a human-centric journey, with accountability and collaboration preserved by design.

  • Mission profiles previously impossible to design - the human can’t be in the moment, but is still in the loop.
  • Edge inference on the vehicle, terrestrial cloud for what doesn’t have to ship; intent and policy travel together.
  • Accountability preserved by design - autonomy is not the same as isolation, even at thirty minutes one-way.
  • Human collaboration scaled across light-minutes, not erased by them.
CTXAGTVALCHG
A voice-driven hazardous-materials classification interface - the system has flagged radioactive alpha contamination, locked conveyor belt C, and is asking the operator to confirm the assessment in their own vocabulary.
Solution spotlight A hazardous-materials production line

The line stops itself - in the operator’s lingo.

Classification used to be the bottleneck on this line: too risky to handle, too dependent on tribal knowledge, too expensive to standardize. The team replaced it with a fully touchless system that listens, watches, and learns from each operator. When something breaks the rules - an off-spec radiation signature, a tag mismatch, a confidence drop - the conveyor halts, the comms channel goes quiet, and the system walks the operator through the call in their own vocabulary.

  • Touchless voice-and-vision interface keeps hands clear of the material entirely.
  • Operators teach the system on the job; classifications get sharper with use, no retraining cycle.
  • Belt halts and comms blackouts are deterministic - capability sits inside guardrails, not next to them.
  • Operators describe the AI as “having my back” - retention and confidence both up since rollout.
CTXAGTDATVAL
A multi-region workforce and scheduling dashboard showing hiring pipeline, compliance posture, weekly schedule coverage across regional centers, and a live operations efficiency metric.
Solution spotlight A multi-region service operator

Local autonomy. Shared rigor. Half a million in licensing back.

A service operator running dozens of regional locations had the classic federation problem - every region wanted (and needed) its own way of working, but without shared documentation, success measures, or AI scaffolding, every region was reinventing the same things and licensing the same tools five times over. Boxcar gave them one substrate where each location kept its operating autonomy on top of standardized intent, success metrics, and an explainable-AI hiring signal a regional GM can actually defend.

  • $500K+ recovered on consolidated licensing in year one alone.
  • Standardized documentation and shared success measures landed across all regions without removing local discretion.
  • Explainable-AI recruiting that hiring leads can defend in plain language - ethics holds up in writing, not just in policy.
  • Compounding gains in talent retention, operational efficiency, customer experience, and risk posture - tracked, not asserted.
CTXDECDATVALCHG
An emergency-department rapid-triage intake screen showing patient identification, an infrared thermal scan deriving heart rate and temperature, and a real-time language-translation panel listening for patient voice input.
Solution spotlight An emergency department

Non-clinical staff. Clinical-grade triage.

An emergency department needed front-desk staff to handle accurate triage on incoming patients without operating outside their training. The team built a multi-modal intake: an IR camera that derives heart rate and temperature from frame-over-frame color amplification, a privacy-respecting lookup against the patient’s prior visits, real-time language translation, and RPA bridges into legacy systems with no API. Every patient outcome feeds historic and real-time analysis - surfaced disparities then become the next features the system ships.

  • Contactless vitals (HR, temperature) from a standard IR camera plus subtle-color amplification.
  • Real-time language translation - born from a disparity the outcome analysis surfaced, not from a feature backlog.
  • RPA bridges to proprietary systems with no API, so urgent data extraction and recording stays within authorized provider workflow.
  • Outcome telemetry feeds the roadmap directly - measurement is the continuous-improvement loop.
CTXDATVALCHG
Get in touch

Ready to put AI on rails?

Tell us about the work you’re trying to bring into a real lifecycle - whether the goal is velocity, evidence, both, or something else entirely. We’ll come back with a real conversation, not a sequence.

A real human will read this

One workflow. Real stakes. Let’s map it.

Whether you’re evaluating an autonomy envelope for a regulated workflow, looking for a workshop for your team, or curious how the open core fits with your stack - this form is the right place to start.

  • Tell us the workflow you’d most like to put on rails.
  • Share the assessment from the readiness check on the home page if you took it.
  • We aim to respond within one business day.
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