Deploy ready Agentic Applications. Build your own when needed.
DMOps helps companies and partners deploy governed Agentic Applications — packaged AI-powered business apps that combine specialised AI crews, local datasets, skills, integrations, deterministic pipelines, automations and audit controls.
Start with ready apps for route risk, invoice matching, field operations, ERP reconciliation, support pulse and executive visibility. Adapt them per tenant, extend them with your own domain logic, and run them with approvals, budgets, permissions and full audit traces.
Join the WaitlistOperations teams don't need another chatbot. They need governed AI crews with clear roles, approvals, and accountability — built for the real world.
AI agents run in silos across sales, warehouse, and delivery — with zero coordination or shared visibility.
Autonomous agents act without budget boundaries, approval gates, or audit trails — creating real operational risk.
Field reps, warehouse staff, and dispatchers can't share tasks with AI — there's no common operational language.
DMOps gives you governed AI crews for real operational work —
a practical path toward Autonomous Field Operations.
Three approaches to AI agents today. Only one is built for real operations across ERP, field apps and humans — with governance, memory and a real org chart.
Agents don't need better prompts.
They need an org chart.
Every DMOps task publishes an immutable artifact. The next agent searches, finds and builds on prior fleet work — instead of starting from scratch every run.
Memory over heartbeats. DMOps agents operate as governed members of a fleet with shared, immutable knowledge — not as stateless one-shot workers.
DMOps is Dynamics Mobile's practical path toward Autonomous Field Operations — adding an intelligence layer that connects field apps, ERP systems, humans, AI agents, IoT signals, approvals and operational data into one governed execution model.
Real-world operations involve money, inventory, customers, vehicles, compliance, documents and people. DMOps helps organizations move step by step from connected operations, to AI-assisted work, to governed AI crews, and eventually to increasingly autonomous field workflows — without losing visibility, accountability or control.
Build once. Deploy across tenants.
DMOps lets teams and partners package industry knowledge into governed AI crews — with roles, skills, tools, tasks, approvals, budgets, integrations and observability built into each solution.
Define the business process, roles, responsibilities, task templates and approval points for a specific industry or customer workflow.
Combine specialized agents, reusable skills, permitted tools, integration rules and operational knowledge into a deployable vertical template.
Run each solution with spending controls, human approvals, audit traces, inbox handoffs and clear accountability from day one.
.dmopsappPackage once, deploy to every tenant. Export to .dmopsapp or push to GitHub. Two-tier tool access queues integration grants for admin approval — your customers stay in control of credentials.
Distributable: Datasets + Skills + Agents + Integrations + Scheduled Tasks, versioned and deployable to any DMOps tenant by you or your partners.
DMOps starts with vertical templates for real operational teams — and gives partners a foundation to create more industry-specific AI solutions over time.
AI crews for route planning, visit preparation, order suggestions, customer follow-up and territory intelligence.
Example: Route Risk Agent, Order Suggestion Agent
AI crews for inventory checks, replenishment signals, picking coordination and warehouse exception handling.
Example: Inventory Check Agent, Invoice Matching Agent
Governed agents for dispatch support, ETA exceptions, proof-of-delivery review and route performance analysis.
Example: ETA Exception Agent, Proof-of-Delivery Review Agent
AI agents that compare ERP, inventory, field activity, payments and documents to detect operational gaps.
Example: ERP Reconciliation Agent, Gap Detection Agent
Daily briefings, approval queues, budget visibility and cross-vertical operational intelligence for leadership.
Example: Daily Briefing Agent, Budget Monitor Agent
DMOps acts as the governed intelligence layer between operational systems and autonomous workflows — connecting agents, humans, tools, ERP data, mobile apps, IoT signals and business rules.
Org-chart-aware access: who can create, approve, deploy and audit — per agent, per tenant.
Model, system prompt, tool set and spending cap per agent — versioned and deployable.
Which agents get which tools and skills — with approval gates before risky tool access is granted.
Kanban-native task management with state transitions, blocking rules and human-in-the-loop handoffs.
Tasks block until a human or supervisor agent approves — budget, data access, deploy decisions.
Per-agent token budgets with hard stops — token pass-through pricing, no model markup.
Every agent action, decision, tool call and human override recorded with full execution logs.
Native plugin system — tools registered at agent init, credentials encrypted, never cached.
Define a prompt and a cron schedule, assign to a role — agent spawns, runs, reports, stops on budget.
An Agentic Application packages everything a governed AI solution needs — agents, skills, tools, datasets, integrations and automations — into a single versioned, deployable unit. Build once. Deploy to every tenant.
Specialist AI workers with defined roles, model profiles, and tool access
Reusable domain knowledge, SOPs, and operational playbooks
Governed access to shell, browser, code execution, and integrations
Structured data sources agents query and humans explore in interactive grids
ERP, CRM, analytics, dev tools — credentials encrypted, never exposed
Scheduled agent runs, prompt → role routing, recurring data workflows
DMOps is multi-LLM by design. Each agent can use the right model for its task — fast and cost-effective models for routine work, stronger models for complex reasoning and planning, and customer-approved models where enterprise requirements demand it.
The platform works out of the box with secure, enterprise-ready model defaults, while also supporting AWS Bedrock, OpenRouter, DeepSeek, Anthropic, OpenAI, Z.ai / GLM, and custom OpenAI-compatible endpoints.
Faster, cheaper models for high-volume work — status checks, data lookups, field confirmations and scheduled report generation.
Stronger frontier models for planning, multi-step analysis, cross-system reconciliation and decisions that need deep context.
Customer-approved or customer-hosted models for scenarios with data residency, compliance or regulatory requirements.
DMOps isn't a silo. Agents reach your ERP, CRM, field apps, analytics and dev tools through a governed integration gateway — credentials encrypted, never exposed to agents.
Plus native communication channels where agents reach humans with handoffs and notifications: Slack, Microsoft Teams, WhatsApp Business, iMessage, SMS.
Agents that touch money, inventory, customers and compliance can't run on trust alone. DMOps enforces zero-trust tool access, encrypted credentials and per-task isolation — by default.
An agent with zero grants sees zero tools. Every integration tool is explicitly approved per agent — no implicit access, ever.
Integration credentials are Fernet-encrypted (AES-128 + HMAC) and decrypted only inside the call, never persisted, cached or exposed to the agent.
Under autonomous mode, an auxiliary LLM risk-assesses each shell command. Catastrophic patterns (rm -rf /, fork bombs, disk zeroing) are hard-blocked even in YOLO.
Every task runs in its own output directory. Agents can't read each other's working files — only shared immutable artifacts.
Agents never modify schemas, create tables, or touch integration configs. They use only the provided API. Violations are flagged for investigation.
New agents start with the minimal toolset — search + file only. Terminal, browser and code execution require explicit grant.
Chat alone can't audit an approval, govern a budget or route a field handoff. Dashboards alone can't act. DMOps introduces AUI — a hybrid agent–human surface built for the operational world.
You can talk to an agent — but you can't audit a conversation, enforce an approval gate, or hand off a structured artifact to a field worker. Conversations don't scale into operations.
Conversational when you need fluidity. Prebuilt UI elements — kanban, inbox, approval queues, artifact viewer, dataset grids — when you need precision, governance and audit. One surface, both modes.
Talk to agents in natural language — steer a running task, ask for clarification, request a different approach. Chat is the fluid layer on top of governed structure.
Humans and AI agents on one task board. Real-time state, priority, assignee, dependencies — no separate "AI system" to chase.
Agent-to-human handoffs routed by role: approvals, budget incidents, exception reports, completed artifacts. Approve, reject, delegate — all in one inbox.
Field workers get handoffs, approvals and artifacts on the go. A purpose-built PWA for sales reps, warehouse staff and drivers — not a desktop shrunk down.
Agents reach humans where they already are: Slack, Teams, WhatsApp, iMessage, SMS, email. Routed by role, not noise.
Every task publishes structured artifacts — reports, analyses, data. Searchable, reusable by the next agent, never deleted. The fleet's shared memory, made visible.
Agents query and surface relational data; humans see it in interactive grids. Define a dataset once — agents read, humans explore, every query is governed.
Every step, every tool call, every token, every cost — traced and replayable. Chain-of-checksum integrity across the whole agent run.
AUI is the new UX for the agentic world — conversational where it helps, structured where it matters, governed everywhere. Built for humans and AI crews to actually work together.
DMOps is created by Dynamics Mobile, a team with 15+ years of experience building ERP-integrated mobile solutions for field sales, warehouse, delivery and last-mile operations.
We dogfood DMOps on ourselves. Our own engineering and operations run on the same platform. Read what happened when an agent tried to fix its own code — and broke through the sandbox.
Read the story →A packaged bundle of agents, skills, tools, datasets, integrations and automations — versioned as a .dmopsapp file and deployable to any DMOps tenant. Think of it as a governed, auditable AI-crew-in-a-box for a specific business workflow.
No. DMOps sits alongside your existing systems — Dynamics 365, SAP, Oracle, custom ERPs, field apps, IoT platforms. It reads data via integrations, makes decisions through governed agents, and writes results back. It's the intelligence layer, not a replacement.
The DMOps agent understands natural language, so you — or your operational users — can describe what you need. The dispatcher routes the prompt through skill matching, org-chart approval gates and budget controls before a specialized agent crew executes the work.
Traditional AI projects need ML engineers, MLOps pipelines, months of development and dedicated infrastructure. DMOps gives you a governed platform where domain experts define the logic — agents, skills, task templates, approvals — and the platform handles execution, audit and cost tracking.
Define a prompt and a cron schedule, assign it to a specific agent or role, and DMOps spawns a governed task on schedule — with full budget control, approval gates and audit trails. Monitor results through the kanban board and execution logs.
The agent stops and requests a budget increase through the approval workflow. A human (or supervisor agent) reviews the progress, checks the cost-to-completion ratio, and decides — approve, reject, or request rework. Budget fencing is built into every agent run.
Yes. Partners get their own access, can build Agentic Applications for their customers, deploy them across tenants, and manage the full lifecycle. The "Build once. Deploy across tenants." model means a solution built for one customer ports to the next with configuration.
Never. DMOps uses provider APIs (OpenAI, Anthropic, etc.) with zero-retention policies. Your operational data — sales routes, ERP transactions, IoT signals — is processed during agent execution and persisted only in your tenant's audit trail and artefacts. No data leaves your control for training purposes.
We're curating an early access cohort. Tell us about your operations — if it's a good fit, we'll reach out to onboard you.
Starts at $49/mo platform fee + token pass-through (you pay exactly what the model costs — we don't mark it up).
We review every submission. If your operations are a good fit, we'll contact you within a few days to get you started.
Governed business agentic apps for real-world operations.