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44 Montgomery St, San Francisco, CA 94104
Across finance, healthcare, telco, manufacturing, and more.
AI use-cases analysed
Business value created
AI solutions deployed
Two parallel streams - technical feasibility and strategic assessment - converge in a prioritised roadmap with working prototypes.
Stakeholder belief audits, data and process review, compilation of 10-20 candidate use-cases.
10-20 candidate use-cases
Each use-case scored against 25+ criteria. Prioritisation matrix produces a short-list of highest-impact, most feasible opportunities.
Prioritisation matrix
Data quality evaluation and a clickable demo of the selected use-case to validate assumptions before committing to build.
Clickable prototype
Implementation timeline with owners, budget estimates, and dependencies.
Roadmap + ROI model
Use-case realisation rate
Scoring criteria per use-case
Typical timeline
AI Use-cases analyzed
CX - BPO
>95% reduction in analyst time on call data
MANUFACTURING
ROI on subsequent implementation costs in less than a year
REAL ESTATE
40+ ideas assessed, 12 prioritized, 3 prototyped
ENTERTAINMENT - iGAMING
100+ ideas distilled to 15 initiatives - 3 imminent priorities
Two parallel streams - technical feasibility and strategic assessment - converge in a prioritised roadmap with working prototypes.
CX • Agentic • Predictive
AI recommendations with agentic drill-down
Hyper-personalized and dynamic reporting
Surfacing direct savings
Design Tooling • Agentic
25+ content block types with live Figma sync
AI-powered spec writing and feature generation
Built for team collaboration
SW Dev. • Agentic
Agent success rate 10 → 90%
Engineering productivity +30-50%
Reduced bug density
Consulting · Agentic · Multimodal
85% recall vs 56% Google Drive vs 46% Gemini
AI sanitization of client names and sensitive data
Research outlining with multi-thread deep research
CX • Agentic
Measured interactions 100%
Deflection Rate Improvement
Reduction in Abandonment
Marketing • Agentic • Predictive
Churn detection 3 months ahead
10 data types analyzed daily
Continous sentiment tracking
$5B Revenue CXBPO
YC Company
$5B Revenue CXBPO
85% recall • 15% analyst time saved
Acquired by ServiceNow
3,000+ brands • 50+ agencies
Complex use-cases combine disciplines — Multimodal extraction feeding Predictive scoring, Predictive triggers launching Agentic workflows.
Team members
Admission rate
They advise. We build. Our strategy engagements end with working prototypes and production roadmaps — not slide decks. Our engineers have credentials from Cambridge, CERN, and Imperial College London. Our strategists come from BCG and McKinsey. You get both in one team.
Neither. We’re an AI services company. We sit at the intersection of AI strategy, engineering, and product. We don’t just advise and we don’t just execute briefs — we own the outcome from use-case mapping through production deployment. Every system runs on a proven delivery platform — battle-tested modules and patterns from 100+ enterprise deployments.
Most companies that come to us with a prioritised list discover the list changes after real technical validation. We can start from your existing roadmap — but we’ll pressure-test feasibility, data readiness, and ROI before building. That’s how we’ve maintained 90%+ realisation rate.
Finance, healthcare, telco, manufacturing, insurance, marketing, entertainment, and CX. 100+ production deployments across these verticals. If you’re in a regulated industry, we’ve navigated the compliance requirements before.
Every engagement builds on what came before. Across 100+ deployments, we’ve accumulated a delivery platform — proven modules, integration patterns, and agent architectures. Your system is custom. The foundation is battle-tested. That’s how we compress timelines without cutting corners.
Both. Sometimes we build custom AI that integrates with your existing stack — CRM, ERP, data warehouse. Sometimes we replace rigid SaaS tools that can’t adapt to your workflows. The approach depends on where the highest value sits.
AI Discovery runs 4–6 weeks and ends with a prioritised roadmap plus working prototypes. Production builds vary by complexity — typically 3–6 months to a live system. Most enterprises start with Discovery and move into production builds and long-term engagements.
44 Montgomery St, San Francisco, CA 94104
