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Consumer Research SaaSAI / Machine LearningSaaS Platform

Incu: An AI-Native Platform for Consumer Sentiment at Scale

How Inventiple built a multi-feature SaaS — combining the UX patterns of Basecamp, GitHub, and Instagram with custom ML sentiment analysis — shipped in 6 months by a 10-engineer senior team.

6 mo
Idea to production
10
Senior engineers
8+
AI-powered features
Multi-LANG
Transcription support
Client
Incu App
Year delivered
2021
Duration
6 months
Team size
10 engineers
Geography
UK / Global
About the client

A market research SaaS for brands that want to actually understand their customers

Incu is a UK-based consumer research and feedback SaaS platform. It exists for one reason: traditional market research is too slow, too expensive, and too disconnected from how consumers actually communicate in 2021 — and beyond. Incu's founders wanted to bring brands, agencies, and end consumers into a single environment where qualitative and quantitative feedback could be collected, transcribed, and analyzed at the speed of the modern internet — not the speed of a focus group.

When Incu's team approached Inventiple, they had a clear vision but no engineering muscle. They wanted a production SaaS — not a prototype — that could compete with established research tools from day one.

The Challenge

A fragmented research stack consumers no longer wanted to use

Brands and agencies were stitching together five or six tools — Typeform for surveys, NPS apps for ratings, video interview platforms, sentiment dashboards, project trackers. Each tool collected one slice of the truth. None of them spoke to each other.

Consumers, meanwhile, were burnt out on traditional research. Surveys felt corporate. Focus groups felt staged. The feedback brands needed was happening on Instagram and Snapchat — in voice notes and quick reactions — but no platform was built to capture that signal at scale and turn it into structured insight.

The Solution

A multi-stakeholder SaaS with AI sentiment built in from day one

Inventiple designed and built a single platform that connects three stakeholder types — brands, agencies, and consumers — with the UX expectations they already had from Basecamp (projects), GitHub (collaboration), and Snapchat/Instagram (fast, native consumer interactions).

Custom ML models, layered on top of AWS Transcribe, run on every text, voice, and video submission. The platform surfaces sentiment, emotion, and theme-level insights as feedback comes in — not in a quarterly report.

The Result

Production SaaS live in 6 months with end-to-end AI pipeline

From kickoff to a production-ready SaaS available to paying brand and agency teams in 6 months, end-to-end. A senior 10-engineer team shipped eight integrated AI and SaaS surface areas — including multi-language transcription, video/audio processing, and a sentiment pipeline — without a single rebuild.

Incu is live today at incu.app and continues to evolve on the foundation Inventiple architected.

6months
Idea to production-ready SaaS
10engineers
Senior-only team, no junior hand-offs
8+features
AI-powered surface areas shipped
100%ownership
Code, IP, and infrastructure to client
What we built

Eight integrated AI and SaaS surface areas

Incu shipped as a single, coherent product — not a collection of features bolted together. Every surface was designed to feel like it belonged.

01

Marketing website

A high-conversion marketing site that introduces Incu to brands and agencies and routes them into the right funnel — research buyer, agency partner, or consumer panelist.

02

Project management tools

Basecamp-inspired project workspaces where brands and agencies plan research, set goals, and align stakeholders before recruiting consumers.

03

Team & customer relations

GitHub-style collaboration surface: teams, roles, comments, and audit trails. Brand teams, agency partners, and consumers each see a tailored view.

04

Machine learning & automation

Custom ML pipelines that classify, summarize, and route incoming feedback automatically. Less manual triage, faster time to insight.

05

Inbox transcription & multi-language

AWS Transcribe + custom post-processing turns voice and video feedback into searchable, taggable text across multiple languages.

06

Video & audio processing & storage

Secure capture, transcoding, and storage of consumer-submitted video and audio at scale. Built to handle thousands of submissions per campaign.

07

Sentiment analysis

Custom models run on every submission, surfacing sentiment, emotion, and theme-level scores in real time. Brands see the signal as it arrives — not in a quarterly slide deck.

08

Deep insights & filtering reports

Interactive dashboards with filtering across campaigns, audiences, and timeframes. Exportable reports for stakeholder presentations.

Technology

Modern, proven, and built to scale

A stack picked for production reliability — and the freedom to evolve the AI layer as the field moves.

Next.js
Frontend
Python
Backend
Django
Backend
MySQL
Database
Redis
Cache
AWS
Cloud
AWS Transcribe
AI
Custom ML
AI
S3
Storage
TypeScript
Frontend
REST APIs
Architecture
Multi-tenant
Architecture
Outcomes

A research platform that lives in the same world as its users

The clearest measure of success on a project like Incu isn't a single vanity metric — it's the fact that the product shipped on time, in production-ready shape, with an AI pipeline robust enough that the founders could focus on go-to-market instead of engineering firefighting.

Six months from kickoff to a paying SaaS. A 10-engineer senior team architected, designed, built, and shipped a multi-stakeholder platform with eight integrated AI and SaaS features. No re-architecting mid-build, no offshore hand-offs, no junior trial-and-error.

A real AI pipeline, not a bolt-on. Sentiment and emotion analysis weren't added at the end as a marketing feature. They were architected into the data model from week one, which is why the platform can surface insights in real time rather than batch-processing them overnight.

Production-grade foundations. Multi-tenant data isolation, AWS-backed file and media handling, and a Django + Next.js codebase that any in-house team could pick up without a long onboarding curve. Incu's team owns the code, the IP, and the cloud accounts in full.

Built to evolve. The ML layer was structured so models could be swapped or extended as the AI landscape changed — a decision that's paid off as Incu has continued to refine its sentiment pipeline over the years since launch.

Want to build something like Incu?

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