An AI prototype can produce a convincing answer while leaving a customer unsure whether to trust it. A B2B dashboard can display every metric and still leave an operations manager hunting for the next action. These are practical design problems for a startup preparing to launch.

For founders releasing a product in 2026 or planning for 2027, the agency search should start with those problems. Onboarding, permissions, information hierarchy and feedback all deserve attention before the team commits to a set of screens.

A portfolio helps when it explains how an agency approached comparable work. Recognizable clients give you somewhere to begin. The useful detail is what the agency contributed, which constraints it faced and how the experience took shape.

FuseLab Creative, Fuzzy Math and Metalab are three agencies worth considering for their published portfolios and named client projects. Their work offers different perspectives on enterprise and public-sector interfaces, B2B research and startup product design. Each provides enough detail to begin assessing the quality of its work against a startup’s needs.

Read the work behind the client name

Look for the users, the original brief and the agency’s responsibilities. A prototype, a brand identity and an application built for release carry different implications for your own project.

For an AI product, pay particular attention to what happens when a result is incomplete, delayed or wrong. Google’s People + AI Guidebook offers a useful reference for expectations, user control and recovery. Bring one situation from your product into the agency conversation and see how the team approaches it.

FuseLab Creative Enterprise interfaces data and AI

FuseLab Creative’s published work spans a financial services company, a state healthcare department and a machine-learning platform. Fiserv, California’s Department of Health Care Services and Grid.ai provide specific projects founders can inspect.

For the Fiserv Small Business Index, FuseLab describes designing and developing an experience for exploring spending trends. Geographic comparisons, business-sector searches and interactive charts had to accommodate changing monthly reports and work on mobile. The design challenge was organizing several ways of examining the same information.

The California DHCS dashboards introduce another audience. Government stakeholders needed to explore long-term services and supports data through geographic and demographic comparisons. FuseLab’s account covers research, interface design and development. Here, the portfolio shows work intended to make specialist information accessible to people with different responsibilities.

Grid.ai, now Lightning AI, brings the discussion directly into machine learning. FuseLab reports designing interfaces and a design system for Train, an experiment-tracking product, and Blueprints, a workflow-automation product. Experiment comparisons and compute-cost visibility were part of the work; Lightning AI’s developers handled implementation.

The connection across these projects is information complexity. A founder building an analytics tool or operational platform can examine how FuseLab organizes comparisons, navigation and detail. For a technical AI product, the Grid.ai work is especially relevant to understanding how the team designs around an engineer’s actual tasks.

Fuzzy Math Research behind complex B2B products

B2B software often carries several people’s priorities into one interface. A buyer wants business value, an administrator needs control, and an employee wants to finish a task. A startup needs to understand where those priorities meet and where they conflict.

Fuzzy Math’s SAP Fieldglass work offers an example. The agency describes a design partnership around enterprise software for managing contingent labor and services, involving customer research, collaboration with executive and development teams, and interfaces across web, tablet and mobile.

For a founder, the interesting part is access to the customer’s organization. Research involving the people buying, configuring and using a product can expose requirements that an internal workshop misses. The Fieldglass account gives a prospective client a concrete engagement to discuss.

The agency’s Field Museum case shows a related skill: deciding what deserves attention. Fuzzy Math reports interviewing more than 40 leaders and developing a framework to prioritize over 80 digital opportunities. Competing requests became a roadmap with an explicit basis for decisions.

That makes Fuzzy Math relevant when a startup has several plausible directions and needs evidence to choose among them. The first conversation should establish what research can resolve, who needs to participate and which decisions the engagement will help the founders make.

Metalab From early prototypes to product identity

Metalab’s portfolio offers a recognizable connection between startup beginnings and established products. Slack, Midjourney and Amazon Photos provide different examples of its contribution.

Its Slack case study describes joining when the application was an early prototype. Metalab helped shape the app, brand, mobile experience and marketing website. That makes the project useful to founders considering how their product’s behavior and identity should develop together.

Midjourney adds an AI example. Metalab lists product design and product strategy as deliverables, and its portfolio describes creating the service’s original interface. The project gives an AI founder a relevant starting point for discussing how users encounter and work with a technical capability.

For Amazon Photos, Metalab describes research with users and design work around storing, organizing, viewing and sharing photographs. The scope follows a connected set of activities, illustrating how a product experience can extend beyond any individual screen.

These projects make Metalab worth reviewing when a startup needs to bring several parts of its product into a consistent experience. Use the case studies to establish which capabilities your engagement needs and how the proposed team would work alongside your developers. The historic client relationship should lead to a discussion about the people available for your project today.

Build a shortlist around your next release

UX Shortlist’s B2B UX design agencies and AI UX design agencies pages can help founders compare relevant work and identify candidates for a conversation. Follow the project evidence and check whether it resembles the challenge ahead.

Give finalists the same brief: intended users, the difficult task, budget, technical constraints and release plans. Request a relevant reference and meet the people who would do the work. Development agencies should also agree how design specifications, implementation questions and later changes will be handled.

Ask the reference what changed after delivery, including problems that required further work or support.

A useful proposal should explain what the team needs to learn, what it will deliver and how progress will be assessed. Those commitments turn an appealing portfolio into something a founder can make a decision on.