Frequently Asked Questions

YUJ brings over 25 years of enterprise UX expertise, helping businesses design intuitive, user-centered digital experiences across industries. Our record is built on deep user research and design work for regulated, complex industries.

We work with enterprise product teams in automotive, fintech, healthcare, banking, retail, and all other emerging B2B services. Our buyers are usually Heads of Digital, VPs of Engineering, CTOs, and product owners at mid-to-large companies in the US and India.

Yes. Our work spans automotive, healthcare, banking, retail, and other emerging B2B services. Where a client can't be named, we share the sector, the problem, and the measurable outcome. To know more, write us at sales@yujdesigns.com.

Yuj's work has been recognised with the Paris Design Awards (2025), Design MasterPrize (2024), NASSCOM SME Inspire Awards (2023), IDA Design Awards (2022), Good Design Chicago (2021), Digital Design Australia (2021), and the Red Dot Design Award (2020). We're also currently nominated across several more national and international categories.

UX strategy, user research, evaluative techniques and audits, UI design, design systems and AI product design, including conversational and agentic experiences. We move upstream from execution into research, strategy, and evaluation. To know more, talk to our strategists at sales@yujesigns.com.

Both. We lead the strategic work (research, discovery, and evaluation) and carry it through to design and handoff, so decisions don't get lost between thinking and shipping.

Our core is design, research, and strategy. We work closely with your engineering and business teams through structured handoffs and can advise on design-to-development workflows so that the built product matches the designed one to achieve the desired business outcomes.

Yes. Alongside project engagements, we can embed senior designers with your product teams for continuous work. This is suitable for scenarios where in-house capacity exists, but strategic design depth is missing.

Yes. A UX or accessibility audit is often the right first step: a focused, strategic starting point to identify where users drop off before scoping a larger engagement.

We begin with discovery and research, move to synthesis and strategy, then design, test, and iterate, and finish with a structured handoff. Every stage is evidence-led, not assumption-led.

It depends on the scope. A focused audit is a matter of weeks, while a full UX transformation runs across several months. We scope realistic timelines at kickoff based on your goals and project complexity.

Yes. We sign NDAs before any detailed discussion and treat client work as confidential by default.

Regular working sessions and clear written updates mapped to the roadmap. You see progress against commitments, not just activity.

Yes and many clients do that. An audit gives you a concrete understanding on your product's UX problems and helps in deciding what to do next.

A polished interface doesn't fix a broken flow. Users abandon products when the underlying experience (the sequence, the logic, the effort required) doesn't match how they actually work.

Most transformations digitise the old process instead of redesigning it around user behaviour. New technology on an unexamined workflow reproduces the same friction on a new screen.

By finding where users struggle and removing that friction before it costs you the user. Research shows what people need; design delivers it in fewer steps, with less doubt.

Because the tool doesn't fit the real task. When a system forces people to fight it, they build spreadsheets and side channels, a clear signal the UX missed the actual workflow.

We work on fixed-scope projects and ongoing retainers, chosen to fit the engagement. We'll recommend the model that matches your problem and timeline.

For teams testing the relationship, a focused audit is usually the smallest sensible starting point. We recommend a starting scope that fits your problem rather than a fixed package.

You do. On completion, ownership of the final design files and IP gets transferred to the client.

The cost depends on the scope, research depth, and timeline. We price based on the problem being solved, not a fixed rate card, and provide a clear scope before you commit.

It varies with method and scale. A targeted usability study costs far less than a multi-market ethnographic study. We recommend the lightest method that answers the question.

Scope, research depth, number of user segments, timeline, and seniority of the team involved. Complex, regulated, or multi-platform products cost more because they demand more rigour.

Senior practitioners lead the work: people who have shipped enterprise products and run hundreds of research sessions, not just written about them.

Senior designers stay involved end-to-end. You don't get a senior pitch and a junior delivery.

Yes, through Skill Labs and our yuj.dna, business capability transformation program designed to prepare professionals for the AI-native era. Built on over 16 years of industry practice and led by Co-founder & Chief Design Officer, Prasadd Bartakke, the program combines Strategic Design Thinking with Human-AI Collaboration to develop AI-native creators equipped to solve real business challenges.

Against the metrics that matter to your business: adoption, conversion, task completion, drop-off, and support load. We agree on the numbers before we start, so success isn't defined after the fact.

Yes. We can share work relevant to your sector, and where a client can't be named, we share the problem, approach, and measurable result.

Yes. We provide structured handoff and stay available during build, so design intent survives implementation.

By tying design changes to business outcomes: more users completing key actions, fewer abandoning, lower support cost. A single friction point removed often pays for the work that removed it.

Yes. When a redesign removes the reason users were leaving, both retention and revenue move. We can walk you through before-and-after results from comparable work.

By framing UX as a revenue and cost problem, not a cosmetic one. Poor UX loses users, inflates support, and slows adoption, each of which leadership already measures in money.

Through research and evaluation (usability testing, session analysis, and heuristic review) that shows exactly where and why people struggle, rather than where we assume they do.

Find the specific steps where users leave, then remove the effort, uncertainty, or dead ends at those points. Drop-off is rarely random; it clusters where the experience asks too much.

By making the product predictable and transparent: clear feedback, honest status, and no hidden behaviour. People trust systems they can understand and anticipate.

Features accumulate faster than the experience is rethought. Each addition makes sense alone, but together they bury the core tasks users actually need.

We map the real end-to-end workflow across systems, find where handoffs break, and redesign around the task rather than the org chart or the software boundaries.

We start with research into how the current system is really used, including the workarounds, then redesign the critical flows while protecting the work people depend on.

Most agencies sell execution: screens and deliverables. We work upstream in strategy, research, and evaluation, where the decisions that make or break a product actually get made.

Most agencies stop at design and delivery. YUJ works upstream, starting with research and strategy. We bring 16 years of enterprise UX practice, a design upskilling programme, and yoxa.ai, our agentic orchestration platform. That mix adds research depth and AI product thinking, not just screens.

We combine 16 years of enterprise UX practice with a design upskilling programme and yoxa.ai, our agentic orchestration platform. That range means we bring research depth and AI product thinking, not just product design.

When you need senior strategic depth faster than you can hire it, or when an outside view can see the friction your team has stopped noticing. Many clients use us to raise the ceiling on an existing team.

Choose a project engagement for a defined problem with a clear endpoint. Choose an embedded team when design work is continuous, and you need senior capacity working alongside your product teams.

It runs across several months, depending on the number of products, users, and systems involved. Real transformation is measured in adoption change, not in a single delivery date.

A focused study takes a few weeks; broader, multi-segment research takes longer. We match the method to the decision so you're not paying for depth you don't need.

It's treating user research as a tool for business decisions, not just design validation. Research tells leaders what will and won't work before they commit a budget to it.

It replaces opinion and assumption with evidence about real user behaviour. Leaders decide faster and with less risk when they can see what users actually do, not what everyone believes they do.

By connecting each insight to a decision and a metric. A finding only matters when it changes what you build, and that change shows up in adoption, conversion, or cost.

Design work which is planned and measured against a defined business outcome (adoption, conversion, retention) rather than against how the interface looks.

Traditional UX often ends at a polished deliverable. Outcome-Driven Design starts from the number you need to move and treats the design as the means to move it.

It's designing AI systems that act on a user's behalf so people can understand, trust, and direct them. The design work sits at the workflow and decision layer, not just the interface.

By making the agent's actions visible and explainable, and by giving users clear control. Users don't abandon AI because it's occasionally wrong. They abandon it when they can't tell when it's wrong.

It's designing AI products so users can see why the system did what it did, in language they understand. Explainability is a UX problem as much as a technical one.

It's designing the point where a product, or an AI agent, makes or supports a decision, so the logic is clear, and the user stays in control.

Because decisions are often buried in engineering logic with no design applied. Users are handed outputs they can't interrogate, so they distrust or ignore them.

Well-designed workflows cut wasted steps, reduce errors, and speed up the decisions that drive the business. Fixing the workflow often does more than any single screen.

By simplifying application flows, qualified users can finish them. Long, high-effort forms lose applicants at exactly the moment they are ready to convert.

Find the steps where applicants quit, usually where the app asks for too much, too soon, then redesign those steps to show value before demanding effort.

By designing search and catalogue systems around how technicians and buyers actually look for parts, not around the internal database structure. Findability is a research and design problem.

Map the real cross-system task, find the broken handoffs and design a coherent flow over them, so users stop stitching systems together manually.

By designing around the needs of both patients and clinicians, healthcare tools become easier to use and more effective. Good UX reduces stress for patients, saves time for clinicians, and helps deliver better care because in healthcare, every interaction matters.

By removing friction from the moments that matter (booking, tracking, and service) and designing for real conditions like poor connectivity and users in a hurry.

It's our structured method for designing AI agents that behave like teammates, not scripts. We work through five stages: framing the right problem in discovery, defining the agent's persona and boundaries, designing its workflow, testing it on real data, and deploying with ongoing monitoring.

Our approach is guided by three core principles: it should interpret intent rather than just follow instructions; it should operate with bounded autonomy and clear decision limits; and every decision should be explainable, with audit trails and human-readable reasoning.

Traditional UX focuses on the interfaces people use. Our MOX-F framework goes further by defining the right agentic problem, agent roles, autonomy boundaries, guardrails, and orchestration to create AI systems that work reliably in real-world environments.

No. AI automates execution, but people still define purpose, make critical decisions, and build trust. The next generation of UX designers will be AI-native creators who use AI as a collaborator while leading it with human judgment.

Designers are moving from designing screens to designing how AI behaves. They decide what an AI agent should do, where it should stop, and how users can trust and work with it. As AI becomes more common, roles are evolving from UX Designer to Agent Designer, AI Experience (AIX) Designer, AI Product Designer, and AI-Native Designer. The focus is shifting from interfaces to AI-powered experiences.

By building the capabilities AI can't replicate: framing problems, tying design to business outcomes, and making sound decisions under ambiguity. Our yujdna programme develops exactly this across three dimensions: strategic product and experience leadership, AI-enabled product creation, and agentic experience orchestration, because tools change fast but the ability to think, decide, and create value endures.

yoxa.ai is yuj's platform for building workflows where teams of AI agents collaborate on complex tasks, using plain natural language so business users can build them without technical expertise. The difference is orchestration over automation: specialised agents coordinate, run in parallel, retry failures, and deliver an end-to-end outcome instead of acting as a single assistant. It also gives you full control over your agents, workflows, and tools, and lets you test on simulated data so no real data is ever put at risk.

Yes. Agents connect to your apps and data, handle formats like PDFs, CSVs, Word, and JSON, and query your databases directly, running either as managed cloud or inside your own VPC.

You can build workflows without writing code, using ready-made templates, a from-scratch builder, or a natural-language prompt that generates the workflow for you. It's built for enterprise B2B teams, with dedicated support, uptime SLAs, and compliance with the DPDP Act, GDPR, and CCPA.