● Capabilities
Six lines of work. Most cases use three or four of them; a few need only one. If none of them fit what you are facing, we will say so rather than sell you the ones that don’t.
A missing-persons timeline is usually a handful of hard timestamps separated by long gaps of assumption. We take the confirmed points — a clock-out, a transaction, a camera hit, a last message — and model what is physically possible between them using real road networks and real travel times.
The output is a minute-by-minute reconstruction with explicit earliest and latest bounds at every step, which matters more than a single best guess: it tells a search team what ground can be ruled out entirely, and that is often the more useful half.
Automated licence-plate readers and public cameras are now dense enough that their silence carries information. If a vehicle passes one reader and never reaches the next, the stretch between them becomes the highest-value search corridor in the case.
We map known reader and camera positions along the relevant routes, identify the unmonitored gaps, and work out which of them are consistent with the timeline. We are explicit about the limits: public camera registries are crowd-sourced and incomplete, and police hold the authoritative reader map. Our analysis tells you where to ask them to look, not what they will find.
This is the work most agencies have neither the tooling nor the analyst hours for. Using public bare-earth lidar, we measure every closed depression along a corridor — how deep it is, how far below the road grade its floor sits, how much canopy or water is over it, and how far it is from any road anyone walks or drives.
Those measurements become a ranked list of ground to search, with the reasoning attached to each entry. Two things we insist on, both learned the hard way: sites in the median or the shoulder ditch are excluded, because a vehicle there is found in the first hour and cannot explain a long search; and standing water is handled separately, because bare-earth lidar returns a flat water surface and a pond is therefore invisible to depression analysis.
Every candidate is checked against current satellite imagery before it reaches you. Terrain data ages — sites get cleared, graded and developed — and a ranked list nobody has eyeballed is a list that wastes a search day.
Systematic sweeps of the public record: NamUs, state missing-person clearinghouses, court and custody records, jail and corrections lookups, professional licensing, property and voter files where they are public, and obituary and cemetery indexes.
The step that gets skipped most often, and matters most in older cases, is cross-matching a missing person against unidentified-decedent and unclaimed-persons records in other jurisdictions. People are found and never connected back to the case that is looking for them.
Establishing what was live and when it stopped: account and username reuse across platforms, last verified public activity, archived copies of pages that have since changed, and reverse image work on known photographs.
Strictly from public surfaces. We do not access accounts, we do not attempt recovery flows, and we do not use pretexting to get someone to open a door for us — see our standards for why that line does not move.
Volunteer searches lose an enormous amount of effort to duplication. Three teams walk the same treeline while an address two miles away is never visited, and nobody has a single view of what has actually been covered.
We build shared live maps for a specific search: ground marked as covered, canvass targets marked as asked or not asked, and the gaps made visible. It is unglamorous and it is frequently the single highest-value thing we deliver.
There is no charge to ask, and we will tell you honestly whether open sources can still add anything to the case.
