AI & Agents · Est. $12k – $15k
Nifty.ai

AI-Powered Reselling Infrastructure

Coralsoft designed, built and shipped this product for the client.

WebNext.js (App Router)ReactTypeScript
nifty-ai.example / dashboard
Nifty.ai — product interface
The situation

What was in place before we started.

Nifty.ai is an all-in-one reselling platform used by thousands of online resellers to crosslist, automate, and analyze sales across major marketplaces.

Nifty.ai is an all-in-one reselling platform used by thousands of online resellers to crosslist, automate, and analyze sales across major marketplaces.

Estimated Engagement
3 months
Team
5 people
Estimated Budget
$12k – $15k
Marketplaces
eBay · Poshmark · Mercari · Etsy · Depop
Scale
Thousands of active resellers
Platform
Multi-platform inventory & automation
Capability
Real-time business analytics
Estimated stack
Next.js (App Router)ReactTypeScriptTailwind CSSTanStack QueryReact Hook Form + ZodVercel AI SDKNode.js + HonoDrizzle ORM + PostgreSQLRedisStripe Checkout + WebhooksVercel
Delivery story

Building Nifty.ai: AI workflows users can understand and trust

01

Challenge

Nifty.ai is an all-in-one reselling platform used by thousands of online resellers to crosslist, automate, and analyze sales across major marketplaces. The main delivery challenge was to give users powerful automation with clear feedback, predictable states, and guardrails around model behaviour, while keeping Source, List, and Crosslist consistent across the complete journey. We framed the engagement around the smallest production-worthy flow first, then expanded the scope without weakening the underlying component and data model.

02

How we built it

We began by mapping the user journey and the boundaries of the AI: what context it receives, what it may return, and where deterministic application logic must stay in control. We then built Source, List, and Crosslist as small end-to-end slices, connecting the interface to the data and model layers early so the team could test real responses instead of static mock-ups. Prompt, validation, and fallback behaviour were refined alongside the product UI. The main implementation used Next.js (App Router), React, TypeScript, and Tailwind CSS, with typed contracts keeping the JavaScript stack consistent across the product.

03

Delivery

The delivered scope brought Source, List, Crosslist, and Automate into one coherent production-ready product experience. Model output, product logic, and user feedback are separated clearly, which makes the AI easier to evaluate and evolve. For Nifty.ai, the practical result is a product that communicates its value quickly while giving the team a maintainable base for continued delivery in ai & agents.

Challenges

Each constraint, and what we did about it.

Constraint

Manual crosslisting across every marketplace

What we did

Unified inventory across every marketplace

Constraint

Inventory duplication & oversell risk

What we did

AI-assisted listing generation & prefill

Constraint

Time-consuming relisting and offer management

What we did

Always-on automation in the cloud

Constraint

Fragmented analytics and bookkeeping

What we did

Real-time analytics and profit tracking

Constraint

Repetitive seller workflows that don't scale

What we did

Operations scale without headcount

Constraint

Growth gated by manual labor or VAs

What we did

Performance-first reseller experience

Resellers needed infrastructure that automated operational complexity without sacrificing control or visibility.

Results

Measured outcomes.

3-month engagement
+32%
Faster reseller listing velocity.
45%
Reduction in manual workflow time.
+22%
Average reseller revenue uplift.
2.1×
Operational efficiency improvement.
+43%
Frontend performance lift
−60%
Repetitive seller tasks
+24%
Analytics feature adoption
+38%
Daily active sellers

By consolidating listing, automation, and analytics into a single AI-powered platform, Nifty enabled resellers to scale operations without proportionally increasing manual effort.

Showcase

How the system fits together.

4 of 7 views
nifty-ai.example
Nifty.ai — product interface
nifty-ai.example
Nifty.ai — product screenshot
nifty-ai.example
Nifty.ai — product screenshot
nifty-ai.example
Nifty.ai — product screenshot
Roadmap

Estimated delivery sequence.

3 months
Weeks 1–3

Discovery & shaping

Discovery, workflow architecture, marketplace integrations, MVP infrastructure.

Weeks 4–10

Core build

AI listing systems, automation engine, analytics dashboards.

  • AI Crosslisting Engine
  • Cloud Automation Layer
  • Analytics & Profit
Weeks 11–13

Launch & iterate

Optimization, additional marketplaces, performance, automation expansion.

  • Frontend Modernization

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