Three local-AI products from our research: one available today, two in early access with design partners. Alongside them, the solutions we build and run for customers.
No product matches those filters yet.
Local-first AI bid and RFP intelligence. Your library never leaves your infrastructure.
Configuration-driven workflow platform for document-heavy and operations-heavy teams.
A local, tool-calling AI specialist that lives as a chat pane inside Excel on Windows.
Proven systems from our engineering work, re-implemented and tailored for a new customer rather than sold off the shelf.
A routes-and-fleet platform for a city bus network, with live vehicle tracking and ridership analytics in one dashboard.
One system of record for a field-services business: people, projects, accounting, payroll, and timesheets.
QR-scan inventory control covering inward and outward movement, purchase and sales orders, and invoicing from one system.
Weekly work and transport planning for field crews, replacing manual dispatch with one scheduling system.
| Guarantee | CrestBid AI | Orchestrator Studio | Vexilo |
|---|---|---|---|
| Runs on your hardware | Fully local on GPU or Apple Silicon. | On-prem GGUF inference, from a laptop GPU up to a shared team server. | Local model (27B) on your machine, via llama.cpp. |
| Human approval before it acts | Every answer is a draft until a human approves it. | Low-confidence or disagreement holds the run for a human review queue. | Additive by default; asks before destructive actions. |
| Audit trail | RBAC and audit trails on every action. | Run history, activity feed, accuracy analytics. | — |
| Offline licence | Air-gap ready: offline licence validation. | Offline signed licence keys. | A signed licence key, verified offline — no network call. |
| Open model weights | Open-weight llama.cpp models by default. | Open-weight GGUF models: Gemma-4-E4B, Qwen2.5-VL-7B. | 27B model, Apache-2.0 licence. |
This is the discipline behind every Mobiprise product, applied through whichever of these steps that product's own mechanisms support. The model's own output is never deterministic, and we never say it is — what's deterministic is the layer that checks it.
Grounded
Answers are drawn from your own documents and data — retrieval, not memory.
Checked
Deterministic rules, lookups, and reconciliation with tolerances check the result before anyone sees it.
Held for a human
Anything uncertain, disputed, or out of policy waits for a person instead of shipping unapproved.
Recorded
An audit-ready record of what was decided, and why — so it can be checked later, not just trusted now.
If none of these fit exactly, our AI-Accelerated Product Engineering team can build it.
