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From conversation to structured data in weeks

We've built our intake process for companies that move fast. No six-month procurement cycles. No RFP theater. A focused process that gets your physical-world operations running quickly and correctly.

Phase 1

Discovery Conversation

We start with a 30-60 minute conversation about your product, your data, and your physical-world needs. This isn't a sales call — it's a scoping session.

What we learn from you:

  • What your AI product does and what data it consumes
  • What physical-world activities you currently handle (or wish you could)
  • Where these activities happen geographically
  • What's working and what's breaking in your current approach
  • What data formats and delivery mechanisms your pipeline expects
  • Timeline, budget constraints, and regulatory requirements

What you learn from us: Whether we're the right fit, a rough sense of how we'd approach the work, and what questions we'd need answered to scope it precisely.

Some clients arrive knowing exactly what they need collected or done. Others need help figuring out what physical-world operations their AI product requires. We serve both. If you're not sure what you need, that's a fine starting point.

Phase 2

Scope Definition

We translate your needs into a precise operational specification. This document becomes the foundation of our engagement — it defines what gets done, how, where, how often, to what standard, and in what format.

The scope document covers:

  • Activities: Exactly what physical-world work will be performed
  • Equipment & methods: What instruments, tools, or techniques will be used
  • Quality standards: Measurable criteria for acceptable work
  • Cadence: How often activities occur (one-time, weekly, monthly, continuous)
  • Geography: Where operations will take place and coverage requirements
  • Deliverables: Exactly what data or outcomes you receive, in what format
  • Data integration: How deliverables feed into your existing pipeline
  • SLAs: Response times, uptime commitments, quality guarantees

You review and approve this document. Changes are incorporated until we're aligned. No ambiguity, no surprises.

Phase 3

Pilot Execution

Before scaling to full operations, we run a limited pilot. This proves the methodology, validates data quality, and confirms that deliverables integrate correctly with your systems.

The pilot typically includes:

  • A small-scale version of the full operation (e.g., one site, one collection cycle)
  • Full data delivery through your actual pipeline
  • Quality review against defined standards
  • Feedback loop to refine protocols before scaling

Most pilots complete in 1-2 weeks. By the end, you've seen exactly what the ongoing engagement will produce, and you've verified it works with your systems end-to-end.

Phase 4

Ongoing Operations

With the pilot validated, we scale to full operations. Your field work runs on the defined cadence, to the defined standard, with the defined deliverables — reliably, consistently, without you thinking about it.

What ongoing operations include:

  • Trained field personnel executing to your operational spec
  • Equipment maintenance and calibration
  • Quality assurance on every deliverable before it reaches your pipeline
  • Regular reporting on operations metrics
  • A dedicated point of contact for scope changes and issue resolution

Phase 5

Structured Data Delivery

We don't hand you a PDF and walk away. Data is delivered in the format your systems consume, through the channels your pipeline expects.

Delivery options include:

  • API integration (REST, webhooks, or custom)
  • Cloud storage (S3, GCS, Azure Blob) with structured naming and metadata
  • Database writes (direct to your data store)
  • SFTP or other file transfer protocols
  • Custom formats matched to your pipeline's expectations

Every deliverable includes metadata, quality flags, and provenance information. Your ML pipeline gets clean, structured, trustworthy input — every time.

Common questions

How long does onboarding take?

Discovery through pilot completion typically takes 2-4 weeks. Simple, well-defined engagements can move faster. Complex, multi-site operations with regulatory requirements take longer. We'll give you a realistic timeline during discovery.

What if we don't know exactly what we need?

That's common and fine. Many clients know they need physical-world operations but haven't specified the details. Part of our value is helping you translate product requirements into operational specs. We'll work through it together during scoping.

What geographies do you cover?

We operate across the continental United States and are expanding. For concentrated operations in a specific metro area, we can staff up quickly. For distributed, multi-site operations, we'll discuss coverage during scoping and propose a realistic plan.

How is this different from hiring a contractor?

A contractor gives you a person. We give you a system. Defined quality standards, backup personnel, equipment maintenance, data delivery infrastructure, SLAs, and a single point of accountability. When your contractor gets sick, your data collection stops. When our field technician is unavailable, another qualified technician covers the work.

What does it cost?

Engagements are priced based on scope, geography, cadence, and complexity. We provide detailed pricing after the scoping phase. There are no hidden fees, and our pricing structure is transparent. Most AI companies find our rates comparable to — or lower than — the blended cost of cobbling together freelancers, traditional service providers, and internal coordination.

Can we start small?

Yes, and we recommend it. The pilot phase is designed exactly for this. Start with one site, one data type, one collection cycle. Validate that it works. Then scale.

Ready to scope your physical-world operations?

Tell us about your AI product and what you need done in the real world. We'll schedule a discovery conversation and get started.

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