AI-Enabled Products | Whitespectre

the challenge

The demo worked. Production is a different problem.

Your competitors are shipping AI features. Your board is asking about your AI roadmap. You need AI woven into your product experience - not a bolt-on chatbot, but intelligent features that make your product genuinely better for the people who use it.

Or maybe you've already started. You launched an AI feature six months ago and it's not moving the needle. It works in controlled conditions but breaks on edge cases, degrades under load, or produces outputs your team can't explain or improve. The gap between a working demo and a production AI feature is where most initiatives stall.

The model is rarely the hard part. The hard part is the architecture around it: how you handle failures gracefully, how you evaluate quality at scale, how you monitor drift, and how you build something your team can iterate on without re-architecting every time the model changes.

our approach

Engineered for production, not just for launch day.

We've shipped AI features that handle 200,000+ messages a day, serve enterprise clients like Banco Santander and Danone, and run in production across 40+ countries. The patterns we apply come from that experience - not from theory.

01

ARCHITECTURE FOR
RESILIENCE

Multi-model orchestration with automatic failover. Dynamic model selection based on cost, latency, and availability. Graceful degradation when things go wrong - because in production, they will. The architecture decisions made on day one determine whether your AI features still work at 10x the users.

02

EVALUATION FROM
THE START

If you can't measure it, you can't improve it. We build observability, evaluation, and traceability into AI features from the beginning - not as an afterthought when something breaks. Turn-level, session-level, and cohort-level: understanding not just whether the AI responded, but whether it helped.

03

MODEL-AGNOSTIC

LLMs evolve fast. We design architectures that let you swap models as capabilities improve, without rebuilding your product around them. Compartmentalised agents with clean interfaces, so the intelligence layer can evolve independently.

04

PRODUCTION
HARDENING

Prompt engineering for consistency across thousands of real-world inputs. Range testing against variable data quality. Explicit UX patterns that make it clear when content is AI-generated. The difference between a prototype and a product is the work that happens after the model works.

01

ARCHITECTURE FOR RESILIENCE

Multi-model orchestration with automatic failover. Dynamic model selection based on cost, latency, and availability. Graceful degradation when things go wrong - because in production, they will. The architecture decisions made on day one determine whether your AI features still work at 10x the users.

02

EVALUATION FROM THE START

If you can't measure it, you can't improve it. We build observability, evaluation, and traceability into AI features from the beginning - not as an afterthought when something breaks. Turn-level, session-level, and cohort-level: understanding not just whether the AI responded, but whether it helped.

03

MODEL-AGNOSTIC

LLMs evolve fast. We design architectures that let you swap models as capabilities improve, without rebuilding your product around them. Compartmentalised agents with clean interfaces, so the intelligence layer can evolve independently.

04

PRODUCTION HARDENING

Prompt engineering for consistency across thousands of real-world inputs. Range testing against variable data quality. Explicit UX patterns that make it clear when content is AI-generated. The difference between a prototype and a product is the work that happens after the model works.

CAPABILITIES

AI capabilities, built for real users.

LLM Integration & Agentic Architectures

Multi-agent pipelines, conversational AI, intelligent document processing. From single-model features to orchestrated agent systems where specialised components handle distinct tasks - with the traceability to debug and improve each one.

Intelligent Search, Recommendation & Personalisation

AI that understands context, not just keywords. Behavioral scoring, real-time recommendations, and personalisation engines that learn from usage and improve over time.

ML Model Training, Deployment & MLOps

From training to deployment to monitoring in production.
The infrastructure to keep models performing as data evolves - not just the model itself.

Computer Vision & NLP

Image recognition, natural language understanding, voice processing, and translation at scale. Production features that handle the messy reality of user-generated content.

AI Performance Monitoring & Iteration

Systematic evaluation frameworks connecting quality measurement to root cause diagnosis. Observability, evaluation, and traceability - so when something drifts, you know where to look and what to fix.

LLM Integration & Agentic Architectures

Multi-agent pipelines, conversational AI, intelligent document processing. From single-model features to orchestrated agent systems where specialised components handle distinct tasks - with the traceability to debug and improve each one.

Intelligent Search, Recommendation & Personalisation

AI that understands context, not just keywords. Behavioral scoring, real-time recommendations, and personalisation engines that learn from usage and improve over time.

ML Model Training, Deployment & MLOps

From training to deployment to monitoring in production.
The infrastructure to keep models performing as data evolves - not just the model itself.

Computer Vision & NLP

Image recognition, natural language understanding, voice processing, and translation at scale. Production features that handle the messy reality of user-generated content.

AI Performance Monitoring & Iteration

Systematic evaluation frameworks connecting quality measurement to root cause diagnosis. Observability, evaluation, and traceability - so when something drifts, you know where to look and what to fix.

AI in production

AI products we've built and shipped.

WhatLingo

An AI Translation App That Understands the Conversation, Not Just the Message

WhatLingo is a companion app for WhatsApp that provides real-time, full-chat translation across 60+ languages. It was conceived and built by Whitespectre and now helps thousands of people worldwide connect across language barriers

From AI Prototype to Production Pipeline in Under Two Weeks

A growing VC fund had pieces of an AI-assisted deal evaluation process - scattered prompts, manual workflows, results they couldn't fully trust. Whitespectre turned that into a production-ready, multi-agent pipeline that evaluates incoming pitches in minutes, not hours.

Whitespectre is a company you can rely on for high-quality, well-architected products.

Rodrigo Guzman

Co-Founder, Hubble_s

Hubble_s

Transforming companies with AI-driven behavioral insights

Leveraging AI, Hubble_s’ SaaS platform offers real-time recommendations, automated behavior scoring, and a digital twin capability, providing organizations with a powerful toolkit for data-driven change management.

From clarity to outcome

Strategy → Outcome

Purple Carrot

Solving startup growing pains for 3x growth and $30M acquisition

With a dedicated technology team and best practice mentoring, Whitespectre supported Purple Carrot in scaling their technology platform from early start-up days to a successful acquisition.

Acting as in-house development team... helped us reach major milestones including acquisition”

Brian Greenfield

CEO, Purple Carrot

Merryfield

Bringing a clean label rewards app from vision to market

Merryfield had a strong vision for a better-for-you rewards app. They turned to Whitespectre to help to bring it to life through product strategy consulting, UI/UX expertise, and an app delivery team.

I couldn't have found a better resource and partner than Whitespectre. They were key on concepting, product strategy, UI/UX and had the technical skills to then make it happen.”

David Mayer

Founder & CEO, Merryfield

Fabletics

Streamlining workflows and enhancing digital experiences for a 75% boost in efficiency

Tech-first Fabletics joined forces with Whitespectre to assess, integrate & customize the best tool to achieve their vision for a more robust & efficient CMS to create captivating digital experiences.

An all-in-one platform to drive clinic revenue and enhanced pet care quality

NYC-based Milo partnered with Whitespectre to evolve their software from MVP to an end-to-end B2B solution powering multiple veterinary clinics.

WHY US

We build products, not prototypes.

We've written about the gap between AI demos and production systems - and we've shipped on the production side of that gap, repeatedly. The difference is engineering rigour: compartmentalised architectures, systematic evaluation, production monitoring, and the discipline to test against messy real-world inputs, not clean sample data.

13+ years of production engineering for platforms serving millions of users (Fabletics: 7M weekly views, Beachbody: hundreds of thousands of users). We apply the same rigour to AI - because an AI feature that breaks at scale is worse than no AI at all.