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 stats page puts the median IoT payback period at 12 months, based on 36 validated deployments. 📡72% of deploymen...
10/28/2026

Our new stats page puts the median IoT payback period at 12 months, based on 36 validated deployments. 📡

72% of deployments paid back within a year, and the fastest broke even in about 4 months. Projects aimed at direct cost reduction clustered between 4 and 9 months. At the 12-month mark, 28% of the sample had not recovered its cost.

More than 70 companies responded to the 14-day survey, and the analysis kept the 36 that reported payback against a stated baseline.

IoT payback period data from 36 validated deployments: a 12-month median, 72% paid back within a year, and cost-reduction projects in 4 to 9 months.

Across 72 companies running AI in production, 96% require human review before AI output reaches a customer, patient, reg...
10/26/2026

Across 72 companies running AI in production, 96% require human review before AI output reaches a customer, patient, regulator, or other external party. ✅

The next most common control, a confidence threshold that routes uncertain outputs to a person, reached 34%. Logging of prompts and outputs reached 28%, mostly in financial services and legal technology, and automated drift monitoring came last at 18%.

With logging at 28%, roughly 7 in 10 deployments keep no record of the prompts a model received or the outputs it returned. Without that record, a team cannot reconstruct a disputed output.



Human in the loop review covers 96% of 72 production AI deployments, while only 28% log prompts and outputs and 18% monitor for drift.

Audit trail and decision reconstruction blocked 12 of 33 AI projects in regulated industries, more than any other barrie...
10/23/2026

Audit trail and decision reconstruction blocked 12 of 33 AI projects in regulated industries, more than any other barrier in our compliance research. ⚖️

The 33 firms work in healthcare, medical devices, fintech, and nearby regulated sectors. Past the largest categories, the barriers spread thin, with 4 separate categories drawing 2 responses each.

The stats page draws on an open-response survey that ran between June and August 2026, with 67 submissions screened down to 33.



AI audit trail and decision reconstruction blocked 12 of 33 AI projects in regulated industries, ahead of data boundaries (7) and data provenance (4).

New research: we asked 40 practitioners where their AI agents run with no person watching, across support, engineering, ...
10/21/2026

New research: we asked 40 practitioners where their AI agents run with no person watching, across support, engineering, sales, and IT operations. 🤖

25.6% of the deployments run unattended, and 32 of 40 respondents had narrowed or switched off an agent after go-live. In 11 of the 32 reported failures, monitoring said everything was fine while the work was wrong.

Katerina Merzlova's study closes with recommendations for teams scaling agents, starting with treating authorship and release as separate decisions, each with its own controls. The full report includes the failure taxonomy and the complete respondent list.



SumatoSoft studied 40 AI agents in production across four functions: 25.6% run unattended and 80% were narrowed after go-live. What breaks, and why.

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

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