Exploratory R&D sprints
Short, focused sprints to validate early ideas. We de-risk sensor choices, connectivity, and data capture before you commit to a full build.
- Technical discovery
- Rapid PoC builds
- Hands-on experiments
Out of the lab. Into the field.
Edge, AI & IoT R&D for real-world environments.
Elysautus Solutions works with teams to turn fragile lab demos into robust prototypes for pilots and field trials. From sensors and gateways to cloud pipelines and analytics, you get end-to-end support without the enterprise burden.
- Focus
- Edge · AI · IoT
- Engagements
- R&D · PoC · Field pilots
- Mode
- Hands-on & collaborative
R&D snapshot
Live prototype
Edge devices
- • Sensor selection & PoC rigs
- • Embedded Linux & containers
- • Gateway orchestration
Cloud & data
- • Data pipelines & storage
- • Dashboards & alerts
- • Pilot-ready architectures
Built with open source, self-hostable stacks wherever possible.
Services
How we go from idea to working prototype
Everything is designed to move fast, learn early, and keep you in control of the stack.
Prototype & field-pilot builds
Turn slides and lab demos into rugged prototypes ready for field testing with real users and real environments.
- Hardware + software integration
- Edge–to–cloud glue
- Monitoring & observability
Architecture & delivery playbooks
Capture the learnings into clear documentation, architectures, and runbooks your team can actually use going forward.
- System architecture
- Ops & deployment patterns
- Knowledge transfer
Process
A simple R&D flow from idea to field-ready prototype
Structured enough to keep everyone aligned; flexible enough to adapt to messy real-world constraints.
Step 01
Discover & frame
We clarify the problem, constraints, and success signals. This is where we separate ‘cool tech’ from what actually needs to work in the field.
- Stakeholder + domain interviews
- System and data flow sketching
- Risk + assumption mapping
Step 02
Prototype in controlled chaos
We build lean prototypes that intentionally stress-test hardware, connectivity, and data pipelines before you commit to a bigger spend.
- Edge device PoCs and rigs
- Cloud + data pipeline scaffolding
- Tight build–test iterations
Step 03
Field pilot & hardening
We run pilots in real environments, capture what breaks, and harden the system so your team has evidence instead of slides.
- Pilot deployment support
- Observability and metrics
- Operational tweaks and tuning
Step 04
Playbooks & handoff
We codify the architecture, decisions, and runbooks so your team (or partners) can extend the work without guesswork.
- Architecture diagrams and docs
- Runbooks and checklists
- Next-steps roadmap
You can plug in at any step: from an early “we’re not sure what’s possible” discovery, to an existing lab demo that needs to become something you can actually deploy and measure outside the building.
Research-backed work
Not just opinions — years of AI, IoT, and HCI work you can actually look up.
AI & Computer Vision
Emerging application areas & challenges of automatic face analysis (Continuum, 2013)
IoT & HCI Prototyping
Applying HCI practices to IoT prototyping (From IoT to Smart Cities, CRC, 2017)
Tele-op UI Evaluation
MSc framework for evaluating object-tracking UIs in tele-operative systems
About
Lab-to-field R&D, without the theatre
I help teams turn promising Edge, AI, and IoT concepts into prototypes that survive real environments — not just conference demos.
The Elysautus playbook was shaped first at Ryerson in Toronto, then replayed in Finland with industry partners: prove it in the lab, then make it deployable, observable, and maintainable in the field.
Today, I use that same approach to help teams move from slides, lab rigs, or conceptual diagrams to pilot-ready systems — with clear constraints, honest trade-offs, and a bias toward open, self-hostable stacks where they make sense.
Read the full story on the About page →Contact
Tell me about the problem you're trying to solve
No sales funnel. Just a straightforward 30–45 minute call to see if I can help.