Three tools.
One database.
DLT is the platform — but it's not the only way data gets in. We also ship a voice-based logger and a field-assist mobile app. All three write into the same shared database, so a sensor reading, a voice note, and a checklist entry can all power the same dashboard.
The ecosystem
Each tool — click to drill in
DLT
Voice Logger aka fieldNix
FieldAssist
DLT — the platform
Owns the data model, the templates, and the dashboards customers actually look at. See the DLT page and architecture for full detail.
What it does
Ingest, transform, store, surface.
Who uses it
All customers — directly or via embedded dashboards.
Status
Mature core. Active development on dashboards, alerts, ML.
Voice Logger = fieldNix (internal name)
Field crews call in to log maintenance. Retell AI handles the conversation; a small Azure serverless layer parses + writes straight to the DLT DB. Tight, single-purpose app — currently live for XRI only.
What it does
Crew calls a number, talks through the maintenance event, hangs up. The record is in DLT before they're back in the truck.
Stack
- Retell AI — voice agent
- Azure serverless — webhook + parse
- DLT DB — destination tables
Who uses it
XRI — sole customer. Tight integration with their maintenance log datastore.
FieldAssist
Mobile app (Expo / React Native) for field crews — runs alongside the desktop dashboards. Same data, different surface.
What it does
Crew workflows — checklists, events, maintenance records, photo capture.
Who uses it
Stack & status
Repo: field-assist-mobile. Specifics & roadmap TBD
Why share a database?
One source of truth
A pump's sensor reading, the crew's note about it, and the model's anomaly score all land in tables that talk to each other. Cross-source dashboards become trivial.
Composability
A new customer might start with FieldAssist only, then add DLT sensor ingestion, then layer ML on top — without rewiring anything.