SumatoSoft

SumatoSoft SumatoSoft helps to improve operations with AI, connected-device platforms, and custom software. What was the idea behind starting this organization?

Please introduce your company and give a brief about your role within the company? SumatoSoft is a custom software development company that focuses on turn-key projects, which means we provide a full range of services, from business analysis and software prototyping to UX design, development, quality assurance and support. At SumatoSoft, we strive to apply cutting-edge technology along with our comprehensive experience, dedication and technical expertise to make sure our customers get solutions that fully meet their business needs. Being a co-founder, not only am I responsible for SumatoSoft’s global strategy but also I am directly involved in managing resources, building and maintaining lasting relationships with customers. Together with Vladimir Shidlovsky, my business partner and co-founder of SumatoSoft, we decided to set up a company that would provide businesses with high-quality custom software and what is more, supports our clients throughout a whole way of their ideas’ implementation. We made Quality the cornerstone of all the company’s activities and adhere to the concept to this day, which allows SumatoSoft to become a technology partner for our customers. What are your company’s business model–in-house team or third party vendors/ outsourcing? We are a dedicated in-house team running like clockwork where everyone plays an important role and contributes to the success of each project and company as a whole. I am proud to say we brought together true masters of their craft. How is your business model beneficial from a value added perspective to the clients compared to other companies' models? Thanks to the path we took, we have managed to provide full transparency to our customers at each stage of our cooperation. SumatoSoft’s clients are able to meet and talk to each team member personally. Other benefits are the team coherence and high development speed, as the team is co-located. What industries do you generally cater to? Are your customers repetitive? If yes, what ratio of clients has been repetitive to you? We have a proven track record of delivering high-quality automotive IT solutions, IoT products, marketing automation & e-commerce software, applications for logistics, to name a few. In general, with adequate resources and a high expertise level, we are able to provide solutions to business challenges in any domain. Speaking about our clients, about 90-95 percent of them are repetitive: once a client has an idea for a new product or service, they turn to the proven technology partner – SumatoSoft. What is more, many businesses come to us on the recommendations of our existing customers.

Our new guide sorts 9 common bank AI use cases by what the rules allow today. 🏦In the US, SR 26-2 replaced SR 11-7 on Ap...
10/19/2026

Our new guide sorts 9 common bank AI use cases by what the rules allow today. 🏦

In the US, SR 26-2 replaced SR 11-7 on April 17, 2026, and it leaves generative and agentic AI to each bank's own framework. In the EU, credit-scoring obligations under the AI Act now start on December 2, 2027, while chatbot disclosure has applied since August 2, 2026.

For each use case, the guide names the evidence an examiner expects. Its evidence pack maps 8 artifacts to the regimes that ask for them. Katerina Merzlova wrote it from primary sources, and the deployment map and evidence checklist come as a downloadable PDF.



SR 11-7 is gone, SR 26-2 skips generative AI, and EU credit-scoring rules start Dec 2027. See which bank AI to deploy now, deploy with controls, or hold.

We're collecting data for a benchmark report on AI budgets at companies with 250 to 2,000 employees, and we need technol...
10/08/2026

We're collecting data for a benchmark report on AI budgets at companies with 250 to 2,000 employees, and we need technology executives who own or share that budget.

The survey takes about 3 minutes and covers project cost, approval, vendors, and results. We report budget figures only in aggregate, and respondents who leave an email address receive a copy of the report. 📊

We'll also add a backlink to your company's website to the research if you'd like to be publicly featured!

Take the survey: https://forms.gle/mxRjEC2Zk4KfiQaHA

Can you forecast a failure on a machine that has never failed? Actually, YES. ⚙️Our new playbook covers the hybrid engin...
09/25/2026

Can you forecast a failure on a machine that has never failed? Actually, YES. ⚙️

Our new playbook covers the hybrid engine we run: gradient-boosted models for equipment with a failure history, paired with anomaly detection for equipment without one. The second half learns what normal running looks like and flags the drift that precedes wear, usually reaching a usable baseline within 14 to 30 days.

Drawn from two deployments: unplanned downtime down close to 50% at a multi-plant manufacturer, and down 38% across 28 turbines at a German wind farm.

95% of AI pilots fail. The cause is usually planning, not the technology used. Read our new article that features a 5-st...
09/24/2026

95% of AI pilots fail. The cause is usually planning, not the technology used. Read our new article that features a 5-step framework - Scout, Score, Scope, Stack, Schedule - for custom AI in 2026.

New research: we asked 33 companies in healthcare, medical devices, fintech, and adjacent regulated sectors what complia...
09/22/2026

New research: we asked 33 companies in healthcare, medical devices, fintech, and adjacent regulated sectors what compliance did to a specific AI project. 📊

19 of the 33 blocking constraints concerned producing evidence. 22 firms redesigned a working system, 5 delayed and then delivered, and 2 abandoned the work. 8 respondents named buyer-side security review as the binding constraint, placing a customer questionnaire above GDPR and SOC 2 in observed salience.

30 of 33 expect a heavier burden within 24 months, and none expect relief. The full study publishes the coding scheme, the screening criteria, the complete respondent roster, and a downloadable PDF.

RAG knowledge platform, commercial propertyFive buildings, five ways of filing the same document. 🏢A US commercial prope...
07/30/2026

RAG knowledge platform, commercial property

Five buildings, five ways of filing the same document. 🏢

A US commercial property operator was running office and mixed-use sites across several cities, each with its own routines. Lease terms, vendor contracts, maintenance records, and compliance documents lived in different systems and different heads, so every tenant or contractor request turned into a hunt.

We built a RAG knowledge platform that pulls all of it into one retrieval layer and answers with citations, so nobody has to trust a black box. Access stays role-based. One place to ask, with the source attached.

https://sumatosoft.com/portfolio/case-study-rag-based-knowledge-platform-for-a-commercial-real-estate-operator

Fintech anti-fraud and underwritingFour data sources, two review paths, one growing manual queue. 🛡️A fintech lender in ...
07/28/2026

Fintech anti-fraud and underwriting

Four data sources, two review paths, one growing manual queue. 🛡️

A fintech lender in Warsaw was pulling signals from a payment gateway, a KYC provider, a credit bureau, and its own CRM, but the flows never met. Some checks ran automatically, others by hand, and the manual review queue grew with every new customer.

We wired those scattered risk sources into a feature store and a decision engine, then put AI scoring into the application and transaction flow. Every decision carries a reason code and an audit trail, so it can be explained. Faster decisions and tighter anti-fraud, with sensitive data handled carefully.

https://sumatosoft.com/portfolio/ai-integration-fintech

What is ADLCSDLC was built for software that behaves the same way twice. AI doesn't. ⚙️Run a probabilistic system throug...
07/23/2026

What is ADLC

SDLC was built for software that behaves the same way twice. AI doesn't. ⚙️

Run a probabilistic system through a process designed for deterministic code and you land in the gap most teams know too well: a pilot that demos beautifully and never ships.

ADLC is our answer. It's a software engineering framework for AI systems with governance built into the lifecycle, not bolted on after a scare. Five pillars and seven phases, from an AI readiness and value check through token economics, secure architecture, red-teaming, and guardrail tuning once the system is live.

The guide also covers when to reach for ADLC and when plain SDLC is still the right call.

https://sumatosoft.com/blog/what-is-adlc-agentic-development

AI adoption success researchWe studied why 95% of AI pilots stall, and what the other 5% do. 📊Most coverage stops at the...
07/21/2026

AI adoption success research

We studied why 95% of AI pilots stall, and what the other 5% do. 📊

Most coverage stops at the gloomy headline. We wanted the pattern underneath, so we collected rollouts from executives, founders, operators, and functional leaders who put AI into production in the last 18 months, and kept only the cases with a baseline and a measured result.

The ones that worked shared a shape: a named workflow, a baseline, one KPI that moved, and a reason the team accepted the change. The model or the vendor mattered less than the workflow it went into.

The piece lays out the KPIs that improved and the barriers behind the failures, where trust came first.

https://sumatosoft.com/blog/ai-adoption-success-cases-in-enterprises

Your LLM bill is not a price table. It's a shape 🧮A SaaS team we worked with budgeted $12,000 a month for an internal co...
07/16/2026

Your LLM bill is not a price table. It's a shape 🧮

A SaaS team we worked with budgeted $12,000 a month for an internal copilot. By month three, it was $34,000. Prices hadn't moved. Conversations ran several turns, people kept hitting regenerate, and a retrieval step quietly stuffed more context into every prompt than anyone had planned for. 💸

Our new framework forecasts LLM spend with ratios that outlive model names. Output runs about 5x the cost of input, and a flagship model costs 15 to 30x an economy one. Agent workflows pile on another 3 to 10x over simple RAG. One formula with six variables, plus five techniques that tend to cut a bill by 40 to 70%. 📊

It ships with a free calculator, so you can put a number on an AI project before you build it. ✅

Address

One Boston Place, Suite 2602 Boston, MA
Boston, MA
02108

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