Mildly AI
Mildly AI
Boring AI that works.

Make the right AI bet. Then make it work.

We help businesses identify high-value AI opportunities, rescue stalled initiatives, and turn them into working products with measurable results. From strategy and feasibility to production delivery, we combine senior product judgment with hands-on AI engineering.

20+ years building technology products
AI expertise from research to production
Startup built and exited
Featured Case Study

From AI research noise to decision-ready intelligence.

A technology intelligence product built and deployed for a sovereign wealth fund with US$100B+ in assets.

Read the Sentio Case Study
Real product walkthrough · 42 sec Deployed AI Product
Applied AI · Research & Intelligence Sentio
The Business Problem

A major sovereign wealth fund wanted AI to scan emerging technology markets continuously for its portfolio companies. Earlier experiments generated generic web summaries and zero actionable signal. Stakeholders didn't need more summaries—they needed decision-ready intelligence.

What We Built

We designed and delivered Sentio: a self-service intelligence system with company strategy dossiers, frozen query plans, relevance gating, and full source lineage.

Measurable Results
~2,800 → ~10
Candidate sources distilled into curated sections in ~20 minutes
5.3 → 9.7/10
Quality score: before Sentio vs. after
149
Newsletters generated in 2 months, across 9 organisations in 7+ industries
Zero edits
First newsletter judged ready to circulate as written
Read Full Technical Case Study
Selected Work

Other projects & systems.

AI products, document intelligence, and enterprise engineering delivery across complex operational domains.

01 / Applied AI & Document Intelligence
AI-Assisted Due Diligence

RiskLens

Product walkthrough · 55 sec

AI-assisted due diligence that analyzes complex documents, extracts relevant information, and helps analysts identify potential discrepancies.

AI architecture · Document analysis · Full-stack

Contract Intelligence Launched AI Product

ClauseCheck

Product walkthrough · 24 sec

AI document understanding that parses complex legal agreements, flags high-risk commitments, and drafts verified clause-level modifications.

AI architecture · Product design · Full-stack

Traffic Operations Prototype

StreetSense

Prototype walkthrough · 47 sec

Turns existing traffic camera feeds into live incident and congestion alerts that operators can review, confirm, and dispatch. AI acts as an analyst inside the operator workflow, not an autonomous decision-maker.

Read the StreetSense case study

Computer vision · Operator workflow · No new roadside hardware

02 / Enterprise Engineering & Production ML
Enterprise Engineering

Enterprise Modernization

Led the technical and product modernization of a mission-critical public-sector platform, rebuilding complex regulatory workflows on cloud-native, workflow-driven architecture under strict operational constraints.

~$40M program · Cloud-native workflow platform · Regulatory workflows

Production ML at Scale

Production Machine Learning

Led development and productionization of scam and fraud detection models with a focus on evaluation, precision, and operational performance.

Scam & fraud detection · High precision & recall · Automated blocking

Advanced AI · Foundation Models

Pioneering Foundation Models for Source Code

Led the development of an AI code-search product, training deep-learning models on 1.7B lines of code so developers could search and understand complex codebases in natural language, years before generative AI went mainstream, scaling to over 100,000 users. Technical approach reviewed by Turing Award winner Yoshua Bengio.

Foundation-model research · NLP · Semantic code search · AI product development

Data & NLP at Scale

Financial Data & NLP Pipeline

Led the rebuild of an award-winning Swiss fintech's NLP and deep-learning pipeline, ingesting over 1 billion social and news messages and serving 250 million API calls of real-time market signals to financial institutions and media, while cutting processing cost and shortening delivery cycles.

1B+ messages ingested · 250M API calls · NLP & deep learning · 50,000+ assets covered

What We Do

Start small. Prove what matters. Scale what works.

Engage at any stage based on your current certainty. Every engagement is structured to create standalone value.

Step 01 Stage

Discover

"Where should we focus?"

Map business workflows, evaluate opportunities against technical feasibility, and identify where AI materially improves cost, speed, quality, or revenue.

Key Deliverable:

Prioritized opportunities, clear business hypotheses, and recommended next steps.

Step 02 Stage

Prove

"Does it actually work?"

Resolve the key uncertainty through focused experiments, technical evaluation, user validation, or a working prototype.

Key Deliverable:

Empirical evidence, evaluation criteria, and a clear go / no-go decision.

Step 03 Stage

Build

"Can we put it into production?"

Deliver validated AI products, integrations, operational workflows, monitoring, guardrails, and adoption support.

Key Deliverable:

A working system with clearly defined operational and business success criteria.

Step 04 Stage

Partner

"Need ongoing execution capacity?"

Embed senior AI/product leadership or deploy a focused AI-native engineering team to accelerate delivery, with senior technical ownership throughout.

Key Deliverable:

Dedicated execution capacity, reliable engineering delivery, and ongoing technical leadership.

A practical place to start

Bring us one workflow, product idea, or stalled AI initiative. We'll help identify the biggest uncertainty, agree on what success looks like, and propose a focused engagement to resolve it.

No broad transformation program required.

Clients can engage at any stage. Each engagement creates standalone value without open-ended commitments.

Who We Serve

Built for teams that need working software, not advisory decks.

We partner with three distinct groups who value senior technical ownership and measurable outcomes.

01 Operating Businesses

Companies

Turn manual workflows and stalled AI initiatives into working software.

Established businesses and scaleups with an expensive operational bottleneck, sluggish workflow, or an AI pilot stuck in 'demo mode'. We take comprehensive technical ownership—from evaluating feasibility to delivering production systems.

Typical Needs
  • Automating complex, document- or data-heavy operational workflows
  • Moving beyond naive LLM prompt wrappers into reliable production architecture
  • Deploying senior AI product execution without hiring a full internal team
Engagement Model

Targeted 2–4 week evaluation sprint or end-to-end production build.

02 Funds & Innovation Arms

Corporate Innovation & Investors

Technology intelligence, diligence automation, and rapid prototyping.

Investment funds, family offices, and enterprise innovation teams that need deep technical evaluation, intelligence systems for market scanning, or rapid validation prototypes for portfolio initiatives.

Typical Needs
  • AI-driven market intelligence and continuous portfolio monitoring (like Sentio)
  • AI-assisted technical and operational due diligence tooling (like RiskLens)
  • Rapid MVP prototyping to validate new venture concepts before capital commitment
Engagement Model

Custom intelligence build, diligence sprint, or portfolio prototype.

03 Agencies & Consultancies

Consulting Partners

Senior AI engineering capacity behind your client relationships.

Strategy firms, design studios, and technology agencies that hold client relationships and enterprise bids, but need specialized AI architecture and delivery capacity.

Typical Needs
  • Co-pitching and structuring technical deliverables for high-stakes enterprise bids
  • Embedded senior AI leadership and white-labeled engineering teams
  • De-risking AI feasibility before committing to client milestones
Engagement Model

White-labeled specialist delivery, co-branded partnership, or technical advisory.

Get in Touch

Have one product or workflow where AI should make a difference?

Let's discuss the business problem, what's been tried, and whether there's a practical next step.

Not sure if AI is the right answer? That's a perfectly good starting point.