Design ServicesEnd-To-End
TDP Rebrand
Sluicebox
AI-powered carbon insights for the electronics industry
- UX / UI
- MVP
- AI
AI-powered carbon
insights for electronics
Sluicebox
ABOUT
Summary
With the goal of transforming carbon data management in the electronics industry, the project aimed to create an AI-powered mission control dashboard that would allow manufacturers and suppliers to easily exchange insights.
Location
USA
Industry
Sustainability
Stage
Seed Stage
We transformed carbon data management with an AI-powered, user-friendly dashboard for manufacturers and suppliers.
sluicebox.ai
E
Total Parts
0
All Parts available across your product portfolio.
Total Manufacturers
0
All Manufacturers supplying parts to you.
Part Data Status
0
Not On Track
0
On Track
0
Completed
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| Part Name | Manufacturer Name | Manufacturing Site | MPN/IPN | Part Family | Part Type | |
|---|---|---|---|---|---|---|
| CAP 22uF 6.3V 0603 | NovaComp | CentraFab, Estonia | NC-CAP-22U-0603 | Capacitors | Multi Layer Ceramic Capacitors (… | |
| INDUCTOR 100nH 0402 | Magnetronix | Plant Z2, Arizona | MG-IND-100N-0402 | Inductors | RF Chip Inductor | |
| DC/DC Converter 5V 2A | VoltEdget | VE Site B, Texas | VE-DCM-5V2A-C1 | Power Modules | Buck Converter Module | |
| ESD Diode 5V Unidir. | ProteQtron | tLine 3, Portugal | PQ-ESD-5V-Z1 | Protection Diodes | ESD Suppression Diode | |
| MCU ARM Cortex-M3 32b | tLogicNova | CoreFab, Taiwan | LN-MCU-32B-F103 | Microcontrollers | 32-bit ARM Microcontroller |
CUSTOMER CHALLENGE
Short Timeline
The team had a tight deadline to deliver the MVP, as they were in talks with potential Fortune 500 clients. Meeting this deadline was critical to building credibility and securing key partnerships.
Key metrics to improve
Traditional carbon tracking in this sector is slow (months per product), costly, inaccurate, and hard to scale due to poor supplier data response and manual effort.
THE APPROACH: DESIGNING SLUICEBOX'S GAME-CHANGING AI MVP
MVP Approach: Focus on Core Features
By clearly defining the MVP scope and using a feature prioritization approach, we ensured that essential was delivered within the tight timeline, while non-critical items were added to the backlog for future phases.
Iterative Feedback Loops Drive Success
Validating early wireframes with users allowed for quick identification of issues and alignment with real user needs. This ensured that the MVP was both user-friendly and aligned with business goals.
Collaboration and Stakeholder Involvement
Close collaboration with cross-functional teams, including stakeholders and users, throughout the design process helped ensure the final product met both business objectives and user needs.
KEY SECTIONS
1
Main Dashboard
The first view of the dashboard had one critical goal: surface the most important information immediately.
To achieve this, we prioritized displaying key metrics upfront, along with clear error states and proactive alerts (e.g., via the AI Auditor flagging issues like data gaps or inconsistencies).
Part Data
CAP 22uF 6.3V 0603Bronze
70% Primary Data
Data Sources
Manufacturer-Sourced 20%
Sluicebox Estimates 20%
Self-Reported 60%
Scope 1 Emissions
Input #1
#Sluicebox AI Estimates#ISO 14607
Input #2
#Primary Data#1404:44
Input #3
#Sluicebox AI Estimates#Self Disclosed
2
Parts Composition
Provides a clear breakdown of materials, sources, and AI-estimated carbon emissions across the full lifecycle (production to disposal).
Highlights key sustainability metrics, emissions hotspots, and AI Auditor alerts for gaps or issues.
3
AI-Agent
The AI agent identifies missing carbon data (e.g., Scope 1, 2, and 3) and automatically generates a request to manufacturers, prompting them to provide the necessary information to suppliers. This streamlines data collection and ensures timely, accurate reporting.
STEP 1/2
CONTACT & INFORMATION
Missing Data Review & Request
Confirm or modify the information below to contact your Manufacturer about the correspondent data.
Send to
jane@email.com
Missing information
You’re missing the following required data:
Site Manufacturing Inputs (Scope 1)
Electricity Inputs (Scope 2)
Material Inputs (Scope 3)
DESIGN IN NUMBERS
Weeks of work2
Screens20+
Features5+
We delivered AI-driven insights and intuitive tools that empower manufacturers and suppliers to optimize carbon data management—achieving up to $3M in average savings per 100 products compared to traditional consultant-led methods.
IMPACT
Results: AI Powered Dashboard in 3 weeks
The MVP for Sluicebox.ai was built and validated in just 3 weeks through direct collaboration with early customers like Vishay Intertechnology, Western Digital, and TTI—delivering immediate, measurable impact that helped secure key contracts with major players in the electronics and semiconductor space (including potential Fortune 500 engagements).
0%
Data coverage
0%
Improved accuracy
0x
Faster processing
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Thank you!