We identify repetitive work, build a practical AI solution, test it with your team, and integrate what produces measurable value—without replacing your existing systems.
Every engagement starts with a specific workflow, a measurable objective, and a small test using real business data.

Kirill Kiryushin
Managing Partner
We don't start with strategy decks. We start with the workflow: where people copy data, search manually, repeat answers, prepare reports, or lose context between tools.
Then we build a small working version, test it with your team, and scale only what proves useful. We connect AI to your existing systems without replacing them.
Every engagement starts with a specific workflow, a measurable objective, and a small test using real business data.
We examine the current workflow, tools, inputs, decisions, and bottlenecks. We interview your team and review existing systems to understand how work actually gets done.
We select a use case with clear value, manageable risk, and measurable success criteria. Each candidate is scored on value, complexity, risk, and implementation effort.
We build a small working version using real documents, data, and user feedback. The prototype is tested with your team to validate feasibility and usability.
We connect the approved solution to existing systems and add human review where necessary. Integration preserves your current tools and adds AI without disruption.
We track time saved, accuracy, cycle time, adoption, exceptions, and business impact. The system is updated as workflows, data, and requirements change.
Illustrative workflow examples showing how AI integrates into existing processes with human review where needed.
Classify incoming requests, retrieve relevant knowledge, prepare a response, and send sensitive or uncertain cases to a human reviewer.
Monitor trusted sources, detect important changes, create source-linked summaries, and notify the appropriate team.
Let employees search approved company documents using natural-language questions while preserving citations and access permissions.
Enrich CRM records, summarize conversations, draft follow-ups, identify missing information, and automate routine reporting.
Transform approved source material into structured briefs, drafts, summaries, and channel-specific content while maintaining editorial review.
Publicly documented enterprise AI deployments – what was automated, and the measured outcome. Every figure links to its original source.
Global enterprise software · customer support
A high volume of routine support questions on the company’s help portal created queues and slow resolution for common issues.
Autonomous AI support agents resolve common questions end-to-end and hand off complex or sensitive cases to human reps.
AI agents now handle roughly half of all support interactions; the support team was rebalanced from ~9,000 to ~5,000 people and support costs fell ~17%.
Major retail bank · fraud & risk monitoring
Scams and fraudulent transactions were hard to catch in real time across millions of daily payments.
Generative-AI monitoring flags suspicious transactions and scam patterns as they happen and warns customers before money leaves the account.
Cut customer scam losses by ~50% and customer-reported fraud by ~30%, while AI-assisted app messaging reduced call-centre wait times by ~40%.
Global bank · legal & compliance
Client-facing teams waited on a small legal department for routine questions, stretching answers out to days.
A legal-assistant GPT, trained on the bank’s own legal documentation, answers routine questions from approved sources and escalates novel matters to lawyers.
Trained on documentation from nine in-house lawyers, it now helps answer 40,000+ client legal questions a year – many in under 24 hours instead of days.
On-the-record statements from enterprise leaders and independent research on the impact of AI automation. Each quote links to its original source.
We are completely convinced the consequences will be extraordinary and possibly as transformational as some of the major technological inventions of the past several hundred years – think the printing press, the steam engine, electricity, computing and the Internet.
Jamie Dimon
Chairman & CEO, JPMorgan Chase
Generative AI is going to reinvent virtually every customer experience we know, and enable altogether new ones about which we’ve only fantasized.
Andy Jassy
President & CEO, Amazon
Today, more than a quarter of all new code at Google is generated by AI, then reviewed and accepted by engineers.
Sundar Pichai
CEO, Google & Alphabet
The consequence of us launching the technology is that we need the equivalent of 700 fewer full-time agents – and the assistant is handling two-thirds of our customer service chats.
Sebastian Siemiatkowski
CEO, Klarna
65% of organizations now regularly use generative AI – nearly double in ten months – and most report real cost reductions in the functions where they deploy it.
McKinsey & Company
The State of AI in Early 2024, Global survey of 1,363 organizations
AI workflow automation uses artificial intelligence inside a defined business process to classify information, retrieve knowledge, generate drafts, analyze data, or recommend actions. Rules, permissions, and human approval remain part of the workflow where needed.
A focused 30-minute conversation to identify your strongest automation opportunities.
A focused conversation about your workflows, tools, and objectives. No generic strategy presentation.
30 minutes
Focused conversation
Specific opportunities
Tailored to your workflows
No strategy deck
Practical next steps only
Join the ranks of industry leaders who have revolutionized their businesses through our cutting-edge solutions.