All Work
AI Agents & AssistantsCustomer support agency

Certainly CX

Creating AI service offerings that help a customer support agency measure quality, assist human agents, and handle phone conversations.

My role
Solutions Architect & AI Solutions Architect
Status
QA product launched and sold; ongoing system support
Categories
AI Agents & Assistants · Data & Decision Intelligence

Outcome

The AI quality assurance product secured its first customer within the first month after launch.

Certainly CX — Quality Analytics — scores, distribution and rubric breakdown. Figures are stand-in data.
Quality Analytics — scores, distribution and rubric breakdown. Figures are stand-in data.

Business context

Certainly CX is a customer service agency supporting other businesses. It wanted to sell new AI capabilities alongside its services — accelerating its roadmap, reducing development costs, and supplementing its existing engineers with a team focused on three new offerings.

The challenge

Certainly CX wanted to introduce AI products it could sell alongside its services, including a way to evaluate agent interactions and identify coaching needs.

The goal: create commercially useful AI capabilities that improve support delivery and provide new offerings for clients.

My role

I served as Solutions Architect and AI Solutions Architect, working directly with the owner on business needs, the solution plan, and priorities. I structured the work with my engineers and kept the owner involved through regular progress updates and delivered outputs.

The team provided product management, design, architecture oversight, and development alongside the client's existing engineering resources.

How the workflow changes

For QA, a support conversation or call enters the system, is evaluated against a quality framework, and becomes a score with coaching opportunities. Leaders review quality trends and decide where agents need help.

The copilot supports the agent during ticket handling, while the voice offering addresses phone interactions. Together, these cover evaluation, assistance, and conversational automation.

Product experience and design

Analytics, coaching priorities, and AI-written daily summaries, in a layout built for wide tables and charts. Design work included more legible success and warning colors, correction of a chart-color collision, and visual regression coverage for page structure.

Architecture and implementation

The QA workflow spans a dashboard, NestJS API, Python scoring service, and Chrome side panel. It queues conversations, redacts personal information before model scoring, and returns results through authenticated callbacks. A multi-tenant structure supports separate customer organizations.

Delivery approach

Assembled Systems contributed design, product management, architecture oversight, and engineering alongside the existing team — a faster, lower-cost development approach than building the offerings in-house.

Results and current status

The quality assurance product secured its first customer within the first month after launch. Assembled Systems continues maintaining and managing systems for existing users.

Palette

Navy

#112130

Sidebar and text

Blue

#225BC6

Primary and info

Red

#FF5655

Brand accent, destructive

Off-white

#FCFAF7

Page ground

Success

#047857

Emerald-700 for legible contrast

Warning

#A16207

Amber-700 for legible contrast

Scope

Published snapshot of the codebase — useful technical context, not a measure of customer impact.

Screens
32
UI components
456
API modules
40
Data schemas
31
Tests
632
Applications
4

Screens

Certainly CX — The dashboard leads with an AI-written daily summary, then the trend and team snapshot beneath it.
The dashboard leads with an AI-written daily summary, then the trend and team snapshot beneath it.
Certainly CX — Coaching priorities, in its empty state — the layout the visual regression suite protects.
Coaching priorities, in its empty state — the layout the visual regression suite protects.

Solution and scope

  • AI quality assurance that reviews calls and email, scores quality, and identifies coaching opportunities
  • A browser-based support copilot that drafts responses across Zendesk, Salesforce, and HubSpot
  • An AI voice agent offering for conversational phone responses and actions

Built with

  • Next.js 16
  • React 19
  • Tailwind 4
  • Redux Toolkit
  • SWR
  • NestJS 11
  • MongoDB
  • Redis
  • BullMQ
  • Python
  • FastAPI
  • Presidio
  • OpenAI
  • Chrome MV3
  • Playwright