AI front desk
Inquiries
Workflows
Human follow-up
SkepticFlow Platform
An AI front desk for service businesses. Public access is currently unavailable. Contact us to discuss your workflow and availability.
Solution Architecture · AI & Automation
We architect systems that think, act, and scale
A solution architecture company helping B2B businesses automate operations, modernize legacy systems, and deploy AI agents - without rebuilding everything from scratch.
From enterprise cloud architecture to intelligent automation: we bridge the gap between what your business needs today and what AI makes possible tomorrow.
Architecture
Design before delivery
Automation
Connected workflows
Azure + AWS
Cloud Platform
B2B + B2C
Enterprise Focus
Products
Products and availability.
Studio delivers custom projects. Check current public access for each product below.
AI and career risk
Cynic
Coach
Concept
AIWhat
A concept exploring AI risk through Cynic and Coach perspectives. Public access is currently unavailable. Contact us to ask about the project.
Career in transition
CV
ATS
Applications
CareerPath101
Build a CV, explore your skills, and track applications. AI features depend on a connected provider.
Services
Two disciplines. One team.
Connect existing systems, evaluate the AI steps that add value, and plan testing, deployment and ongoing operations together.
AI & Automation
AI Agents
Bounded AI tasks with explicit tools, approval rules and evaluated handoffs.
›Support drafting with a human escalation path
›Inquiry classification with an exception queue
›Document extraction reviewed before system entry
Business Process Automation
Connect repeatable work using rules, with tested AI interpretation where useful.
›Email-to-CRM with duplicate protection
›Reconciled recurring reports with flagged missing data
›Document extraction and validation with reviewer ownership
RAG Systems
Retrieve permission-filtered sources and evaluate answers; sources do not guarantee correctness.
›Knowledge search with citations and freshness checks
›Support drafting with abstention for unsupported questions
›Policy lookup with access controls and human escalation
AI Integration
Add a tested AI step to existing systems with defined fallback and operating limits.
›Search evaluated against representative queries
›Classification with confidence review and corrections
›Analysis drafts checked against agreed metric definitions
Architecture & Engineering
Solution Architecture
Assess business constraints, integration boundaries and acceptance criteria. Compare options and record decisions before selecting a design.
›Architecture review and optimization for scaling teams
›Technology selection and vendor evaluation
›System design for new product launches
Cloud Architecture (Azure)
Compare Azure hosting options against agreed security, recovery, availability and operating-cost goals. Test the chosen recovery and deployment approach before relying on it.
›Multi-region Azure deployment with disaster recovery
›Cost optimization of existing Azure infrastructure
›Hybrid cloud architecture for regulated industries
Microservices & API Design
Assess whether service boundaries improve the system compared with a modular application. Define authorized APIs, compatibility and operating ownership before splitting services.
›Monolith decomposition strategy and execution
›API-first architecture for partner integrations
›Event-driven architecture for real-time data flows
System Modernization
Plan staged changes with data reconciliation, cutover criteria, rollback and restore tests. Agree disruption limits and validate them rather than promising uninterrupted operation.
›Legacy .NET to cloud-native migration
›Database modernization with tested cutover and rollback
›Gradual strangler-fig pattern implementation
DevOps & CI/CD
Automate the agreed build, test and release steps with approval gates, observability, rollback checks and named operational responsibility. Measure delivery performance against a baseline.
›Azure DevOps / GitHub Actions pipeline setup
›Infrastructure as Code with Terraform or Bicep
›Monitoring and observability stack implementation
Practical automation
Automate the work between your systems.
Start with one repeated task. Agree how to measure success, connect the tools you already use, and keep people in control of decisions that need approval.
Use rules for predictable steps and AI where a message or document needs interpretation. Test that step before relying on it.
Workflows to explore
Route inquiries
Email or form → check duplicates → classify → create a CRM task for the right team. Unclear requests go to a person.
Prepare documents
Document → extract fields → validate required information → flag discrepancies for an authorized reviewer before system entry.
Keep customers informed
Verified system event → check channel permissions → send a reminder or status update. Include a clear human contact and opt-out.
Prepare recurring reports
Agreed data sources → reconcile → calculate defined metrics → deliver a report with missing data and exceptions flagged.
Move approvals forward
Request → notify the responsible person → record the decision → continue only after the required approval.
Plan for the work after launch
Agree the process map, integrations, access rules, representative tests and operating guidance. Name who handles failures, and define alerts, limited retries and an exception queue. Repeating a run must not create duplicate actions.
Measure completed work
Compare completed tasks, corrections, elapsed time and operating cost against an agreed baseline. Time released is separate from realized financial savings. The proposal identifies recurring platform fees and support scope.
Before you automate
- Do we need AI?
- Often, rules and existing integrations are enough. Use AI only where interpreting variable text or documents adds value.
- Will it work with our current tools?
- First check available APIs, permissions, vendor terms and data quality. Explain access limits before committing to an integration.
- Who approves important actions?
- Define who may approve commitments, payments, sensitive changes and external publication. AI can prepare work without unrestricted authority.
Which task repeats, what starts it, which systems are involved, and who checks the result?
Discuss a workflow to automateHow We Build
Architecture patterns we deliver
Every project starts with a clear system design. Here are the core patterns behind our solutions.
AI Agent Architecture
Conceptual agent loop. Define tool authorization, approval, time/cost bounds and failure handling separately; optional memory must obey access and retention rules.
1 / 5
Components
- User / Trigger
- Orchestrator
- LLM
- Tools & APIs
- Memory Store
- Action / Response
Connections
- User / Trigger connects to Orchestrator
- Orchestrator connects to LLM
- Orchestrator connects to Tools & APIs
- LLM connects to Memory Store
- Tools & APIs connects to Action / Response
- Memory Store connects to OrchestratorDashed connection in the diagram
Why Work With Us
Not another generalist agency. A team that connects the dots.
You need a partner who understands your existing infrastructure deeply enough to introduce AI where it actually matters — and architect it to last.
Architecture-first thinking
Agree the problem, constraints and success checks first. Compare architectural options and document the decisions that affect delivery and maintenance.
Technical review and accountability
Name the technical decision owner and agree the review scope, engineering checkpoints and escalation path. Assess proposed changes against the project’s acceptance criteria.
AI matched to the task
Evaluate AI on representative tasks, limit access to data and tools, and define human review. Use a measured pilot before extending the workflow.
Business translator
Explain alternatives, cost assumptions and risks for both business and technical audiences. Agree what evidence will demonstrate that the work meets its purpose.
Clear delivery ownership
Name delivery and operational contacts, record handoffs and define who handles incidents and exceptions. State the support scope in the proposal.
Long-term partnership mindset
Agree documentation, training and maintenance expectations early. Make dependencies, recurring vendor costs and responsibility for future changes explicit.
Platform
Ask about the Platform.
Public access and the interactive demo are currently unavailable.
The live demo is unavailable right now.
Tell us what you would like to automate and ask about current availability.
Project examples
Explore the workflow. Define the evidence.
The illustrative examples below explain possible designs and what to measure. They are not verified client results.
AI Agent
AI-Powered Support Agent with RAG
Illustrative example — not a client result
Reviewed:
Problem
A support team repeatedly answers questions from a changing knowledge base.
Solution
Retrieve only documents the requester may access, include sources, and hand unsupported questions to staff. Evaluate answers and permitted actions separately before a pilot.
What to measure
- Resolution and repeat-contact rates over an agreed window
- Unsupported answers and successful human handoffs
- Source freshness, permission failures and cost per resolved request
Automation
Email-to-CRM Automation Pipeline
Illustrative example — not a client result
Reviewed:
Problem
Incoming email must reach the correct CRM owner without duplicate or missing records.
Solution
Check message IDs, validate required fields and route using rules. Use a tested AI classification step only when needed. Queue uncertain messages and failed CRM writes for staff; replay with duplicate protection.
What to measure
- Routing accuracy on representative messages
- Duplicate records, queue age and recovery completion
- Elapsed processing time, staff corrections and operating cost
Modernization
Legacy System Modernization (.NET -> Cloud-Native)
Illustrative example — not a client result
Reviewed:
Problem
A legacy application is difficult to change and its dependencies are poorly understood.
Solution
Compare incremental changes to the existing application with managed containers and service extraction. Use a staged migration, data reconciliation, rollback criteria and restore tests; choose Kubernetes only if requirements justify it.
What to measure
- Deployment lead time and failed-change rate
- Availability measured over a defined period
- Restore results and total operating cost against the baseline
Process
Structured execution. No surprises.
A proven process that reduces risk and keeps all stakeholders aligned from day one through delivery.
01
Deep-dive into your business context, technical landscape, and objectives. We map existing systems, identify bottlenecks, and define what success looks like — before writing a single line of code.
Stakeholder interviews and requirements gathering
Current architecture assessment
Risk and constraint analysis
Scope definition and prioritization
Maintenance planning and support scope
Service description and SLA definition
Ongoing service description support
02
Translate business requirements into a clear technical blueprint. Every component, integration point, and data flow is documented and reviewed before implementation begins.
System architecture design
Technology selection and justification
Integration strategy and API contracts
Architecture Decision Records (ADRs)
03
Build in iterative sprints with regular checkpoints. You see working software early and often — not a big reveal after months of silence.
Iterative development with 2-week cycles
Continuous integration and automated testing
Regular demos and progress reviews
Documentation written alongside code
04
Production deployment with monitoring, documentation, and knowledge transfer. Your team can maintain and extend the system independently.
Production deployment with rollback strategy
Monitoring and alerting setup
Technical documentation and runbooks
Team training and knowledge transfer
What's Included
Everything you need. Nothing you don't.
Every engagement comes with these standards built in — not as add-ons.
Architecture-First Approach
Every project starts with proper system design — not jumping into code. This means fewer rewrites and solutions that actually scale.
Full Documentation
Architecture decision records, runbooks, API docs, and handoff guides included with every delivery. Your team can maintain it independently.
Direct Communication
You work directly with the architect — no project managers, no telephone game. Slack, email, or weekly calls — your choice.
Production-Grade Quality
CI/CD pipelines, automated testing, monitoring, and observability come standard. Not as upsells — as part of every delivery.
Transparent Pricing
Fixed-price or retainer — always scoped upfront. No billable-hour surprises, no scope creep without your approval.
Post-Delivery Support
Every project includes a support period after delivery. Optional monthly retainers available for ongoing maintenance and evolution.
Engagement Models
Flexible ways to work together
Choose the engagement model that fits your needs. All models include the same quality standards and direct communication.
Project-Based
One-time engagements with fixed scope, timeline, and pricing.
- Scoped proposal within 48h
- Fixed price — no surprises
- Full documentation & handoff
- 2-week post-launch support
- Source code ownership
Highlighted
Monthly Retainer
Ongoing architecture, development, and AI expertise on demand.
- Dedicated hours per month
- Priority response (< 4h)
- Architecture reviews & consulting
- Continuous improvement & new features
- Monthly progress reports
- Flexible scope adjustment
Advisory & Audit
Short strategic engagements for assessment, review, and roadmap.
- 1–2 week engagements
- Architecture review
- AI readiness assessment
- Security & compliance audit
- Prioritized action plan
- Executive summary
Founder-led
Built by people who run this in production.
Viacheslav Dovnich
IT Solution Architect & Founder
I build SkepticFlow because service businesses do not need louder dashboards. They need systems that answer customers, route work, and leave a trace when something matters.
My background is enterprise architecture, Azure, .NET, and AI delivery. The practical rule is simple: if it cannot survive real customer traffic, it is not done.
LinkedIn
Galyna Goncharova
Customer Success Manager
Leads customer success initiatives focused on helping clients implement, adopt, and scale products after purchase — from onboarding strategy through long-term retention and expansion.
Guides customers through technical and operational challenges, monitors customer health, and drives sustainable growth by elevating the overall customer experience.
LinkedInFAQ
Frequently asked questions
Answers to common questions about working with us.
We start with a free 30-minute discovery call to understand your challenge. If there's a fit, we deliver a scoped proposal within 48 hours — with clear deliverables, timeline, and pricing. No surprises.
Both. We work with B2B companies of all sizes — from funded startups launching their first AI feature to enterprises modernizing legacy systems. The approach scales, the quality doesn't change.
We offer fixed-price project engagements and monthly retainer options. Every project starts with a detailed scope so you know exactly what you're paying for. No hourly billing surprises.
Absolutely. We specialize in integrating with existing systems — not replacing them. Whether it's .NET, Azure, AWS, or legacy on-prem infrastructure, we design solutions that work with what you have.
It depends on scope. An AI strategy assessment takes 1–2 weeks. A custom AI agent is typically 4–8 weeks. Cloud migrations and major system modernizations can take 6–16 weeks. We always provide a timeline upfront.
Yes. Every project includes a handoff period with documentation and knowledge transfer. We also offer monthly support retainers for ongoing maintenance, optimization, and new feature development.
We're architects first, not just developers. Every engagement starts with understanding your business goals and designing the right system — not jumping into code. This means fewer rewrites, lower costs, and solutions that scale.
We're based in Poland and work with clients across Europe. All communication is in English. We overlap with CET/CEST timezone and are flexible with scheduling for UK and US-based teams.
Let's Talk
Have a project in mind? Let's discuss.
Whether you need an AI agent, a cloud migration strategy, or a full system architecture review — we're available for long-term B2B engagements and strategic consulting.
Prefer a direct conversation?
hello@skepticflow.com Connect on LinkedIn
Request a discovery call
Send your project details through the contact form. We typically reply within 24 hours on business days to arrange a free 30-minute call.
What happens next?
- 1 We review your message and respond within 24h
- 2 Free 30-minute discovery call to discuss your project
- 3 Scoped proposal with timeline and pricing within 48h
Based in Poland · Working with clients across Europe · CET/CEST timezone · English, Polish, Ukrainian, Russian