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We identify where AI agents can eliminate routine work. You get a working prototype, production-grade architecture, and a clear financial model before full-scale implementation.
in 8 weeks
Launch your first AI agent
Fixed price: $30,000
AI Sprint — a structured program for launching AI agents
Launch your first AI agent in 8 weeks
First results in 8 weeks
Production-grade architecture
Fixed price and guarantees in the contract
Why does it work?
Clear metrics
for fact-based scaling decisions
$30,000
budget
8
weeks
Uncertain
outcome
$150,000
budget
6-12
months
What is an AI Sprint?
AI Sprint is a fast, controlled way to decide whether AI automation is worth the investment. In 8 weeks, you get the evidence you need to make an informed decision. Then 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 operate in your environment. We define what it processes, what it does autonomously, and where human input is required.
Analyze
1
whether part of the work can be automated or whether efficiency can be improved across the process.
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, and messengers
Selects tools based on context
Performs actions in systems
Saves time on common questions
Shows information
Follows “if–then” rules
Answers FAQ questions
AI agent (Sprint outcome):
Chatbot:
Creates a ticket, fills in the 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 schedule)
Evaluate results against KPIs
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, and dependencies.
Financial model (ROI/TCO): costs, expected impact, constraints, and scaling options.
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 the AI Sprint is for
no access to data, or the data cannot be used
no decision-maker is involved during the pilot
the task is not clearly defined
the ability to work with real data and systems
a decision-maker who can approve the outcome
clear business task
We are confident in the outcome, therefore:
We hand over all deliverables. Code, requirements, architecture, and calculations remain with you.
Scope, timelines, and success criteria are fixed before start
If you scale with EORA, the main implementation contract price will be 30% lower.
FAQ
No. The agent automates routine and repetitive processes, freeing your team to focus on higher-value work. It makes people more productive rather than replacing them.
No. During the Sprint, the agent connects to a test environment, or sandbox, to avoid risk to real data. It is deployed to production only after the scaling plan is approved.
We check the economics before scaling. The Sprint compares implementation and operating costs with the expected impact: time saved, workload reduction, quality improvements, and volume. If the numbers do not justify scaling, you can stop at the prototype stage with the findings and recommendations.
Infrastructure costs depend on usage, scale, security, and hosting requirements. We bill infrastructure separately from the Sprint fee so the cost is transparent and based on actual needs.
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 you. This allows you to continue development and scaling independently, if needed.
No. You will receive a prototype, a clear understanding of automation opportunities, and scaling recommendations you can use in the future.
During testing, we use a sandbox environment. Access to real data is limited, and production integration happens only after your approval.
The AI Sprint includes process analysis, AI agent development and configuration, basic integrations, and a working prototype. Infrastructure and any work outside the Sprint scope are billed separately.
You can start with a minimal dataset: calls, chats, internal instructions, CRM data, or other available process records. If the data is not enough, we will help you to gather missing information.
Yes. We work with public-sector clients and projects with higher security requirements, including on-premises deployment when needed.
