AI workflow automation that fits the way your business works

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.

$35M+
Value Delivered
50+
Clients Served
14+
Years Experience
98%
Client Retention
About Amalgama

Practical AI implementation,
backed by real outcomes

Every engagement starts with a specific workflow, a measurable objective, and a small test using real business data.

Kirill Kiryushin, Amalgama founder

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.

14+
Years Experience
50+
Clients Served
$35M+
Client Value
Services

AI implementation built around real workflows

Every engagement starts with a specific workflow, a measurable objective, and a small test using real business data.

How we work

From repetitive work to a reliable AI workflow

01

Discover

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.

02

Prioritize

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.

03

Prototype

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.

04

Integrate

We connect the approved solution to existing systems and add human review where necessary. Integration preserves your current tools and adds AI without disruption.

05

Measure and improve

We track time saved, accuracy, cycle time, adoption, exceptions, and business impact. The system is updated as workflows, data, and requirements change.

Example AI workflows

How AI fits into real business workflows

Illustrative workflow examples showing how AI integrates into existing processes with human review where needed.

Customer Support

Classify incoming requests, retrieve relevant knowledge, prepare a response, and send sensitive or uncertain cases to a human reviewer.

1Classify incoming requests by type and urgency
2Retrieve relevant knowledge base articles
3Draft a response using approved source material
4Route sensitive or uncertain cases to a human reviewer

Research and Intelligence

Monitor trusted sources, detect important changes, create source-linked summaries, and notify the appropriate team.

1Monitor trusted sources for relevant changes
2Detect important developments using AI
3Create source-linked summaries automatically
4Notify the appropriate team via alerts

Internal Knowledge

Let employees search approved company documents using natural-language questions while preserving citations and access permissions.

1Employees ask questions in natural language
2AI retrieves answers from approved documents
3Responses include source citations
4Access permissions are preserved throughout

Sales Operations

Enrich CRM records, summarize conversations, draft follow-ups, identify missing information, and automate routine reporting.

1Enrich CRM records with relevant data
2Summarize sales conversations automatically
3Draft follow-up emails and identify next steps
4Automate routine CRM reporting

Content Operations

Transform approved source material into structured briefs, drafts, summaries, and channel-specific content while maintaining editorial review.

1Transform approved source material into briefs
2Generate drafts and summaries
3Produce channel-specific content variants
4Maintain editorial review before publishing
Proven in enterprise

Documented results, not marketing claims

Publicly documented enterprise AI deployments – what was automated, and the measured outcome. Every figure links to its original source.

Customer Support
Sector

Global enterprise software · customer support

Challenge

A high volume of routine support questions on the company’s help portal created queues and slow resolution for common issues.

Solution

Autonomous AI support agents resolve common questions end-to-end and hand off complex or sensitive cases to human reps.

Help portal · CRM · knowledge base
Rolled out through 2025

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%.

Source: Salesforce (Benioff) / CNBC, 2025
Research & Intelligence
Sector

Major retail bank · fraud & risk monitoring

Challenge

Scams and fraudulent transactions were hard to catch in real time across millions of daily payments.

Solution

Generative-AI monitoring flags suspicious transactions and scam patterns as they happen and warns customers before money leaves the account.

Real-time transaction monitoring · customer alerts
Reported 2025

Cut customer scam losses by ~50% and customer-reported fraud by ~30%, while AI-assisted app messaging reduced call-centre wait times by ~40%.

Source: Commonwealth Bank, 2025
Internal Knowledge
Sector

Global bank · legal & compliance

Challenge

Client-facing teams waited on a small legal department for routine questions, stretching answers out to days.

Solution

A legal-assistant GPT, trained on the bank’s own legal documentation, answers routine questions from approved sources and escalates novel matters to lawyers.

Internal legal knowledge base · ChatGPT Enterprise
2025

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.

Source: BBVA / OpenAI, 2025
Industry perspective

What leaders say about AI

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.

JD

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.

AJ

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.

SP

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.

SS

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.

M&C

McKinsey & Company

The State of AI in Early 2024, Global survey of 1,363 organizations

FAQ

Frequently asked questions

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.

Get started

Get a Free Workflow Assessment

A focused 30-minute conversation to identify your strongest automation opportunities.

Free Assessment

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

A focused 30-minute conversation. No generic strategy presentation.

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