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We verify where AI agents will truly eliminate routine work in your processes. You get a working prototype, production architecture, and a precise economics model—before a major implementation.
in 8 weeks
Launch your first AI agent
Fixed price: 30 000 $
AI Sprint — a managed format for launching AI agents
8 weeks before the result
Production-grade architecture
Fixed price and guarantees in the contract
Why does it work?
CLEAR METRICS
to make scaling decisions based on facts
30000 $
budget
8
weeks
UNCERTAINTY
it’s hard to predict the outcome upfront
150 000 $
budget
6-12
months
What is an AI Sprint?
A fast and controlled way to decide whether investing in AI automation makes sense. In 8 weeks you make a management decision, and we:
Measure and test
4
where the agent helps the team work faster and with less stress
Build
3
a working AI agent that performs real actions on your data (not just in a slide deck)
Design
2
how the agent will work in your environment: what it sees, what it does autonomously, and where a human is needed
Analyze
1
whether a part of the work can be automated or efficiency can be improved across a set of processes
Karcher
Purina
AVON
Purina Friskies
question quiz
7
Breed recognition
messages
2 343
audio messages
78 434
photos
175 435
Alice interactive
Promo code finale
Personalized feeding
CRM integration
Sila Sveta
Schneider Electric
users
1,044
Engineer tool
messages
approved
1 140
997
Typo tolerant
Smart search
Support relief
Action hub
receipts
20K+
Purina Friskies
Chatbot in the widget on the Purina promo site and main site
Goal:
Centralize the Friskies promo campaign flow on the website and reduce the burden on support.
Solution:
A chat widget on the promo page and the main Purina site that guides users through the campaign (quiz → review → receipt upload), answers FAQs, and escalates to an operator when needed.
Outcome:
The bot became the hub for key on-site actions; during the campaign users uploaded 20,000+ receipts
AVON
Chatbot for selecting gifts for men
Goal:
Deliver a fast, shareable gift-picker experience in VK for a women-focused Feb 23 campaign
Solution:
A chatbot featuring Timur Rodriguez: users upload a man’s photo, AI classifies the "type" and recommends a matching Avon product with humorous, personalized commentary.
Outcome:
Strong campaign engagement — 175,435 photos, 78,434 audio messages, and 2,343 messages recorded during the activity.
Schneider Electric
Bot for searching the technical reference guide
Goal:
Speed up handbook search and help engineers quickly find the right products and specs.
Solution:
A chatbot that accepts queries by product name/properties, searches the knowledge base and returns a ranked list of relevant answers; includes typo-tolerant trigram search and a structured table built from the original PDF.
Outcome:
A pilot "search engine" for highly specialized technical content — a practical tool for design engineers.
Sila Sveta
Chatbots for sending messages "into space" (Signal Festival)
Goal:
Let festival visitors send messages to an installation and "into space" while keeping moderation and throughput under control.
Solution:
Two Telegram bots: the user bot collects messages and runs automatic checks, while the second bot routes content for manual moderation in the client’s channel.
Outcome:
In 3 festival days 1,044 people used the bot; users sent 1,140 messages, with 997 approved and "sent to space."
Purina
Dog food selection: breed recognition by photo
Goal:
Support Purina "21 Days" participants and help dog owners transition to a new food with personalized guidance.
Solution:
A VK chatbot integrated with Purina CRM: identifies breed from a photo, collects pet details, builds a feeding plan, enrolls users into messaging, and sends tips (email/push) plus a discount coupon.
Outcome:
A personalized nutrition journey with ongoing touchpoints that keeps users engaged throughout the program.
Karcher
Quiz in Alice about cleaning (Skill)
Goal:
Engage users with an interactive experience, teach cleaning tips, and finish the flow with a discount promo code.
Solution:
An Alice skill built as a quiz: 7 questions with 4 answer options, helpful feedback after each choice, and a compact numbered list format so all options fit in one message.
Outcome:
A light "learn + play" promo mechanic that keeps attention and naturally leads users to the final promo code.
AI agent = next level of automation
Unlike chatbots, AI agents don’t just answer—they perform actions in systems.
Takes over an entire process step
Integrates with CRM, 1C, Jira, email, messengers
Chooses tools depending on context
Performs actions in systems
Saves time on common questions
Shows information
Works by “if → then” rules
Answers from FAQ
AI agent (Sprint outcome):
Chatbot:
Creates a ticket, fills in fields, and notifies the owner
"To create a ticket, follow the link…"
Weeks 7–8
Weeks 4–6
Weeks 2–3
Week 1
AI Sprint timeline (fixed dates)
testing and scaling decision (evaluate results and KPI compliance)
build a working AI agent (3 weeks)
design (describe agent logic and scenarios)
process and KPI selection (define the goal and success criteria)
What you get at the end of the AI Sprint
Roadmap to production: stages, timelines, resources, dependencies.
Financial model (ROI/TCO): costs, impact, constraints, and scaling points
Solution diagram and requirements for security and integration with internal systems
Proof-of-concept that performs the target task in real processes on your data.
Who AI Sprint is for
no access to data or it cannot be used
no decision-maker during the pilot
task is only an idea
possible to work with real data and systems
a decision-maker who confirms the outcome
clear business task
We are confident in the outcome, therefore:
We hand over all artifacts—code, requirements, architecture, and calculations remain with you
Scope, timelines, and success criteria are fixed before start
If scaling with EORA, the main contract price will be 30% lower
FAQ
No. The agent automates routine and repetitive processes, freeing the team for important tasks. It makes people more productive rather than replacing them
No. At the sprint stage, the agent connects to a test environment or a "sandbox" to avoid any risk to real data. It only goes into production after the scaling plan has been approved.
Infrastructure is a secure and scalable environment for the agent to operate in. We separate the cost of the prototype from the cost of the environment to ensure reliable operation in production.
We build the business case around specific processes. Often, automating routine tasks increases productivity and saves time for important decisions, which ultimately makes implementation worthwhile.
An AI sprint is a new format for implementing an agent in 8 weeks, but it is based on experience from real projects and ready-made tools adapted to the client's specific tasks.
Yes. All scenarios, documentation, and the prototype remain with the client. This allows further development and scaling to continue independently of our involvement.
No. You will receive a prototype, an understanding of the automation possibilities, and recommendations for scaling that can be used in the future.
During the testing phase, we use a "sandbox." Access to real data is limited, and integration into production only occurs after approval from the client.
