AI AGENTS
Evaluate with real workflows
Define expected outputs, sources, permissions, and approval points. Test normal workflows and exceptions before expanding the scope.
A clear path from challenge to working AI
Business discovery and engineering move together. Use evidence from each phase to shape the next, from the first prototype through operation.
DEVELOPMENT PROCESS
Define · Validate · Build · Evolve
Make each next step informed by evidence. Scope and deliverables are agreed for each project.
- 01
Define workflows and team readiness
Review workflows, team skills, and development environments to define in-house development goals.
- 02
Select tools and methods
Select tools and AI that non-engineers can use, and validate feasibility with a small prototype.
- 03
Build together and transfer skills
Co-develop business applications and AI agents while sharing design and implementation skills.
- 04
Prepare for internal operation
Validate quality, permissions, and approvals, then prepare documentation and training for internal operation.
- 05
Support independent improvement
Support the team’s ongoing changes and improvements through reviews and technical guidance.
- 01
Understand operations and challenges
Understand operations, existing systems, and team challenges to agree on shared priorities.
- 02
Define architecture and delivery
Align technology, requirements, and responsibilities in a practical validation and development plan.
- 03
Develop as part of the team
Join the company’s team as a development lead to drive AI and application design and implementation.
- 04
Validate and deploy
Validate quality and usability in real workflows, integrate with existing systems, and deploy.
- 05
Improve and retain knowledge
Improve from operational feedback and share design decisions and development practices with the team.
- 01
Define device and site conditions
Review devices, sensors, connectivity, latency, and operating conditions to define AI’s role.
- 02
Validate data and models
Collect and prepare field data, compare models and runtimes, and evaluate accuracy and processing load.
- 03
Tune and deploy AI on devices
Build or tune models for the task and develop on-device inference and business-system integration.
- 04
Test in real conditions
Test accuracy, latency, and stability on site, and define exception handling and operating procedures.
- 05
Improve with field data
Continuously improve models, settings, and applications using operational feedback and new data.
- 01
Define tasks and robot constraints
Review the robot, tasks, and surroundings to define motions and evaluation criteria.
- 02
Build the simulation environment
Recreate robots and workspaces in simulation with sensor and physics configurations.
- 03
Validate cognition, motion, and AI
Validate cognition and motion, prepare training and evaluation data, and tune AI for the robot.
- 04
Evaluate the simulation-to-hardware gap
Review simulation findings and, where needed, assess differences through hardware tests under defined safety conditions.
- 05
Iterate and improve
Refine environments, data, models, and motion based on evaluation findings to guide further development and research.
PHYSICAL AI
Define conditions and repeat the test
Document devices, data, environments, and test conditions. Distinguish simulation findings from what still requires hardware validation.
WORKING TOGETHER
Before we start
Do we need finalized requirements?
No. A description of the challenge and intended users is enough to begin the discussion. Consulting can define requirements and the development plan.
How do you determine scope and cost?
We review the target workflow, data, integrations, environment, and evaluation needs, then agree on scope, deliverables, roles, schedule, and an estimate.
Can you work with our internal team?
Yes. For AI agents, we offer in-house development support and FDE. Regular discussion, demos, and joint implementation do not require full-time on-site residency.
What should we share initially?
An outline of the problem, the intended use, and the available data or environment. Confidential details can follow an NDA.
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