Syntero
At Syntero, I developed an AI generator to streamline the process of browsing electronic components and finding valid alternatives. This tool aimed to enhance efficiency and accuracy in analyzing datasheets.
User Research
To ensure the AI generator met the precise needs of its users, I conducted thorough research:
In-depth interviews: Engaged directly with engineers and procurement specialists to uncover their workflow intricacies, pain points, and specific requirements in component selection.
Observational Studies: Shadowed users in their work environments to gain firsthand insights into their daily processes, decision-making criteria, and interactions with datasheets.
Design and Prototyping
User-Centered Design Process
Defining User Flow: Mapped out the user journey from component search to selection based on research insights.
Building Wireframes: Created detailed wireframes to visualize interface structure and functionality.
Prototyping and Testing: Developed interactive prototypes for user testing, refining based on feedback to ensure usability and effectiveness.
User Flow
The user flow involves users inputting specific criteria to search for electronic components, leveraging AI-driven analysis to suggest alternatives, and facilitating side-by-side comparison for informed decision-making
Searching Data on a Specific Item
Users begin by entering specific criteria or part numbers into talkin Maxwell the smart AI agent. Maxwell retrieves detailed information from a vast database, presenting users with comprehensive data sheets, including specifications, availability, and pricing from multiple suppliers.
Requesting Valid Alternatives
When faced with obsolete or unavailable components, users can request alternative suggestions through Syntero. Using advanced algorithms, Syntero analyzes parameters such as compatibility, performance metrics, and cost-effectiveness to propose the best-fit alternatives
Validating Data in Actual Datasheets
Upon selecting a preferred alternative, users can seamlessly validate the suggested data by accessing and comparing it with the actual datasheets provided by suppliers. This ensures accuracy and reliability in the decision-making process, mitigating risks associated with component compatibility and performance.
