MESH
A visible autonomy graph
Agents, sensors, robots, conditions, recovery paths, and bounded loops remain visible instead of disappearing inside prompts.
- Selected branches only
- Bounded robot actions
- Structural validation
Beta complete · Operational releaseRobotics · Defense · Governed autonomy
Command autonomous systems.Keep humans in control.
Design, deploy, and supervise agentic workflows that connect sensors, models, robots, and operators. Enforce policy before action, pause at authority gates, and retain an auditable record from mission intent to field execution. Governed by design.
Autonomy GraphAgents, robots, sensors, policy gates
Command AuthorityHuman release, hold, and abort
Mission InterfacesAPIs, telemetry, operator UI
Built for sovereign robotic operations
- Human command
- Policy-enforced autonomy
- Bounded robot action
- Full mission trace
02Governed autonomy
Agentic intelligence. Deterministic control. Human command.
Every consequential behavior has a visible place: the mission agent, the graph, the authority gate, the robot adapter, or the execution record.
AGENT
Governed mission agents
Give each agent an assigned role, approved context, model, tools, knowledge, and a versioned place in the control plan.
- Scoped capabilities
- Approved context
- Versioned profiles
AUTH
Human command authority
Treat release, hold, correction, escalation, and abort as first-class mission steps with an accountable owner.
- Approve or deny
- Pause and resume
- Controlled handoffs
ASSURE
Mission assurance at runtime
Use robot state, execution context, and durable checkpoints to verify what happened before the next field action begins.
- Action-level evidence
- Durable checkpoints
- Explicit safe failure
Aerial perception / governed release
See the operating envelope before autonomy moves.
Correlate terrain, infrastructure, sensor evidence, and platform state in one operational picture. The workflow can recommend a route; command authority decides when the machine proceeds.
- Sensor
- Aerial ISR
- Policy
- Geobounded
- Release
- Human command
03Robotic mission patterns
Start with one bounded autonomy pattern.
These are reference control patterns, not claims of fielded missions. Each one defines the human authority boundary before autonomy is expanded.
Multi-robot tasking
Turn an authorized objective into a reviewable fleet plan without allowing an agent to task a platform on its own.
- 01Receive objective
- 02Assess fleet state
- 03Plan assignments
- 04Commander release
A commander releases robot tasking
Sensor-to-decision
Fuse incoming telemetry, classify uncertainty, and route a recommendation while the response decision stays visible.
- 01Accept sensor event
- 02Correlate evidence
- 03Check confidence
- 04Duty review
A duty officer authorizes the response
Autonomous inspection
Convert platform health signals into an inspection plan while keeping safety limits and engineering approval explicit.
- 01Read telemetry
- 02Diagnose anomaly
- 03Check safety envelope
- 04Engineer approval
An engineer releases the inspection task
04Mission stack
Connect intelligence, machines, and command without hiding the boundary.
NowFlow coordinates the configured systems around a robotic mission without assuming that every sensor, model, platform, or network shares the same trust boundary.
01
Mission inputs
- Robot telemetry
- Sensor events
- Operator tasking
- Approved intelligence
02
Governed autonomy
- Mission agents
- Policy rules
- Fleet coordination
- Human command gates
03
Control runtime
- Graph validation
- Selected path execution
- Durable checkpoints
- Safe failure states
04
Operational surfaces
- Command workspace
- Robot adapters
- Mission APIs
- Embedded operator UI
Authority before autonomy
Platform safety, hosting, network access, identity, model providers, credentials, data classification, retention, and audit requirements are mission inputs—not assumptions hidden behind an autonomy label.
Review our security posture
Platform state / durable evidence
Every machine action leaves a physical and digital trace.
Bind sensor state, agent reasoning, authorization, and the resulting robot command to the same mission record—so field behavior can be understood, replayed, and assured.
- Platform
- Field robotics
- State
- Checkpointed
- Evidence
- Mission trace
05Command views
The right operational picture for every role.
Operators need focus, autonomy engineers need complete control, and assurance teams need evidence. Each role gets the same truth at the right level of detail.
01Mission operator
Command the mission, not the middleware.
See the current objective, fleet state, recommendation, confidence, and authority action without interface overload.
02Autonomy engineer
Make every machine action legible.
Design the graph, configure agents and adapters, test branches, and inspect the same runtime state operators see.
03Assurance lead
Review the full chain of authority.
Trace versions, model decisions, approvals, robot commands, and failures without rebuilding the mission from separate tools.
06Deployment path
Prove one governed robotic mission first.
A focused working session can expose the real authority boundary, missing evidence, integration constraints, and failure modes that a polished autonomy demo can hide.
- 01
Bring one bounded mission
Choose a robotic operation with known platforms, inputs, outputs, and a decision that must remain under human command.
- 02
Map the authority envelope
Identify robot capabilities, models, identity, network, geospatial limits, review, and deployment constraints up front.
- 03
Prove the path in simulation
Exercise nominal, denied, degraded, and recovery paths before deciding whether the operating envelope should expand.
07Questions
Define the command boundary before deployment.
The useful starting point is a shared understanding of machine capability, human authority, data, execution, and the field environment.
01What does governed agentic autonomy mean?+
It means agents may interpret, plan, and recommend inside explicit workflow constraints, while policy gates and accountable humans determine which robot actions can be released.
02Does NowFlow replace the mission operator or robot controller?+
No. NowFlow coordinates agentic reasoning, deterministic control flow, and human authority around existing systems. The organization defines which actions are automatic, supervised, or always operator-released.
03How are unsafe branches and loops constrained?+
Only the selected condition, router, or error edge becomes active. Repetition uses explicit bounded loop metadata, and structurally invalid graphs are rejected before execution.
04Can NowFlow connect to robots, sensors, and mission systems?+
Workflows connect through configured APIs, tools, data sources, and platform adapters. Each connection remains subject to the credentials, protocol, network, and operating boundaries you authorize.
05How should a defense or field deployment be evaluated?+
Start with platform safety, network access, identity, model providers, data classification, retention, audit, latency, and hosting constraints. Prove the control path in simulation before field use.
06Can I send sensitive material through the demo form?+
No. Use the form only to describe the workflow at a high level. Do not include classified, export-controlled, personal, or otherwise sensitive data.