Artificial Intelligence (AI) Software Development Services
Custom AI built on solid software, by a team that has shipped both for 14+ years.
What AI services does SumatoSoft offer, by ROI tier?
The right AI tier depends on where you stand today: your budget, how ready your data is, your compliance exposure, and how complex your operations are. We organize AI work into these tiers and weigh the risk, the return, and whether each step is feasible in production.
Tier 1: AI readiness & consulting
Tier 2: RAG systems & copilots
Tier 3: Agentic workflows development
Tier 4: Custom AI models development
Tier 1: AI readiness & consulting
We pressure-test your business goals before you spend a dollar on development. Before we build anything, we check whether AI actually pays off for your specific use case.
We audit:
- Data availability and quality.
- Infrastructure and integration constraints.
- Security and compliance exposure.
- Operational workflow impact.
- Projected token consumption and cloud costs.
Tier 2: RAG systems & copilots
We connect AI securely to your own business knowledge. This is where most companies start production AI. We build retrieval-augmented generation (RAG) systems and copilots that tap your internal documents, ERP, CRM, and knowledge bases.
They run inside isolated cloud infrastructure (VPC), answer only from verified sources, cite where each answer came from, and enforce role-based access at the data layer. This tier turns static knowledge into working intelligence, and it never trains public models on your data.
Tier 3: Agentic workflows
This tier is for companies ready to automate complex processes that cross departments. Once AI stops just answering questions and starts running workflows, orchestration becomes the hard part.
We govern each workflow with evaluation pipelines, adversarial testing, and cost simulations before it goes live. The multi-agent systems we design retrieve data, reason over your business rules, call APIs, trigger downstream actions, and hand off to a human whenever confidence drops too low.
Tier 4: Custom AI models development
This tier usually suits organizations that process large volumes of data or work under heavy regulation. For them, we design and deploy private model strategies.
That includes fine-tuning small and large language models (SLMs and LLMs), adapting them to your domain, hosting them privately on AWS, Azure, or on-premise, routing between models, and optimizing token costs.
AI that delivers business value
Contact us and get a roadmap tailored to your needs.
What is the AI pilot & prove program?
Our pilot & prove program is a structured 4-6 week engagement that tests three things before full deployment: whether the system works technically, whether your operations are ready for it, and whether it makes economic sense. Rather than experiment in a vacuum, we build a secure, production-realistic environment using a controlled slice of your real data and infrastructure.
What we build
Inside an isolated cloud sandbox (VPC), we connect AI to your internal systems through secure middleware and set role-based access controls at the retrieval level.
We configure a deterministic RAG architecture so every response is grounded in a real source, set benchmarks for accuracy and consistency, simulate real user workflows, and project your monthly token consumption under realistic load.
You get to see how the system performs under real operating conditions.
What you get
At the end of the pilot & prove phase, you walk away with:
- a validated architecture blueprint
- documented security and governance controls
- measured retrieval accuracy and response benchmarks
- a production token-consumption forecast
- a rollout roadmap with cost projections
- a clear investment model for scaling.
Your leadership team can judge the initiative on hard data, projected costs, and measurable outcomes.
What AI has SumatoSoft built?
The system has produced a significant competitive advantage in the industry thanks to SumatoSoft’s well-thought opinions.
They shouldered the burden of constantly updating a project management tool with a high level of detail and were committed to producing the best possible solution.
I was impressed by SumatoSoft’s prices, especially for the project I wanted to do and in comparison to the quotes I received from a lot of other companies.
Also, their communication skills were great; it never felt like a long-distance project. It felt like SumatoSoft was working next door because their project manager was always keeping me updated. Initially.
We tried another company that one of our partners had used but they didn’t work out. I feel that SumatoSoft does a better investigation of what we’re asking for. They tell us how they plan to do a task and ask if that works for us. We chose them because their method worked with us.
SumatoSoft is the firm to work with if you want to keep up to high standards. The professional workflows they stick to result in exceptional quality.
Important, they help you think with the business logic of your application and they don’t blindly follow what you are saying. Which is super important. Overall, great skills, good communication, and happy with the results so far.
They are very sharp and have a high-quality team. I expect quality from people, and they have the kind of team I can work with. They were upfront about everything that needed to be done.
I appreciated that the cost of the project turned out to be smaller than what we expected because they made some very good suggestions. They are very pleasant to work with.
Rivalfox had the pleasure to work with SumatoSoft in building out core portions of our product, and the results really couldn’t have been better.
SumatoSoft provided us with engineering expertise, enthusiasm and great people that were focused on creating quality features quickly.
SumatoSoft succeeded in building a more manageable solution that is much easier to maintain.
When looking for a strategic IT-partner for the development of a corporate ERP solution, we chose SumatoSoft. The company proved itself a reliable provider of IT services.
Thanks to SumatoSoft’s can-do attitude, amazing work ethic, and willingness to tackle clients’ problems as their own, they’ve become an integral part of our team. We’ve been truly impressed with their professionalism and performance and continue to work with the team on developing new applications.
We are completely satisfied with the results of our cooperation and will be happy to recommend SumatoSoft as a reliable and competent partner for development of web-based solutions
Together with the team, we have turned the MVP version of the service into a modern full-featured platform for online marketers. We are very satisfied with the work the SumatoSoft team has performed, and we would like to highlight the high level of technical expertise, coherence and efficiency of communication and flexibility in work.
We can confidently say that SumatoSoft has put all our ideas into practice.
Why SumatoSoft: our pragmatic guarantees
We bring engineering discipline and commercial sense to every engagement. We don’t treat AI as a cure-all. We look at your architecture, your data, your risk, and your costs first. Then we tell you where AI belongs and, just as honestly, where it doesn’t.
We will NOT bolt an LLM directly to your core database.
We design secure middleware and API abstraction layers that shield your legacy systems from instability, latency, and injection attacks.
We will NOT use your proprietary data to train public models.
Your data stays inside your own controlled infrastructure. We deploy AI in secure, isolated cloud (VPC) environments with strict access controls and full auditability.
We will NOT push AI where it does not create business value.
If a deterministic, traditional build gets you the result faster and cheaper, that is what we recommend. We are dual-engine engineers. We build AI that earns a return and structured software that keeps things stable.
Can you add AI to our legacy systems?
AI works best on top of solid software, not in place of it. We take the systems you’ve built up over the years and add an intelligent layer on top, without tearing out what already works. We can do this because we’ve shipped traditional software for over 14 years. That makes us a dual-engine firm, with classic engineering and modern AI under one roof.
How does SumatoSoft engineer production AI? (ADLC)
Traditional software follows deterministic logic: meet a condition, and a predefined action runs. AI systems work differently. They generate responses from probability, context, and learned patterns. That difference calls for its own engineering discipline, the agentic development lifecycle (ADLC).
We define the business goal before we pick a single model. Together we pin down the workflow you want to improve, the outcome you’ll measure it against, and the decision the AI will support. Then we map your data. We find where the knowledge lives, how it moves between teams, and where we’ll need to connect structured and unstructured sources. From day one, the system aims at a target you’ve defined.
A probabilistic system needs hard boundaries, which we call guardrails. We decide which sources it can draw on, how it reaches your data, who is allowed to see what, and when it should refuse to answer at all. These rules aren’t bolted on afterward. We build them into the architecture itself, and it plugs into your ERP, CRM, data warehouses, and internal tools, with full logging and an audit trail throughout.
We measure how the system behaves before anyone outside the test group touches it. Our evaluation pipelines, including frameworks built for retrieval-augmented generation (RAG), check whether answers stay faithful to the source, whether retrieval lands on the right material, and whether the system responds consistently and accurately against the thresholds we set. Nothing scales until the numbers clear the bar.
Production brings scale, simultaneous users, and edge cases the test environment never sees. To stay ahead of them, we attack the system on purpose, red-teaming it and simulating prompt-injection attempts to find where it breaks. We confirm it holds up under load, that each interaction costs what we projected, that it doesn’t disrupt neighboring systems, and that it behaves predictably no matter how users phrase their requests. Only once it proves reliable under real conditions does it move to production.
Going live doesn’t end the oversight. We keep watching answer quality, how current the data stays, how people actually use the system, and what it costs to run. When we adjust it, we document every change and tie it back to where your business is headed. The system improves on purpose, and you can measure that improvement.
How does SumatoSoft secure enterprise AI?
AI systems have to run inside clear technical, legal, and operational boundaries. We build those boundaries straight into the architecture rather than adding them later.
Infrastructure-level security
We deploy AI inside your own controlled cloud, AWS or Azure, using private networking, isolated workloads, and encrypted data flows. Access runs on fine-grained, role-based permissions that match your internal policies.
Data governance by design
We decide how data is taken in, processed, stored, and accessed before any model integration starts. The system can redact or mask sensitive information automatically, and it enforces access policies at both the application and retrieval levels.
Compliance alignment
Our delivery processes follow ISO 27001 and support regulations such as GDPR and the EU AI Act where they apply. We build documentation, audit trails, and model-lifecycle transparency into the development process itself.
Operational oversight
We build in monitoring, logging, and performance tracking from day one, so you can trace model outputs, system behavior, and infrastructure usage across every environment.
Which industries does SumatoSoft build AI for?
We’ve delivered AI development across more than 20 industries, building custom, industry-specific software for both new and established businesses. Our work spans big-data analysis, AI development, and machine learning, and we’ve already created value for more than 350 companies worldwide.
Retail
- personalized product recommendations;
- inventory forecasting and management;
- dynamic pricing optimization;
- customer behavior analytics;
- AI-powered virtual assistants and chatbots.
Manufacturing
- predictive maintenance and asset optimization;
- AI-powered quality inspection and defect detection;
- robotic process automation (RPA);
- supply-chain forecasting and planning;
- automated quality assurance.
Ecommerce
- AI-assisted search;
- speech recognition services;
- relevant offers for buyers
virtual agents and intelligent automation tools; - personalized shopping experience.
Since 2020, AI has gone from an emerging trend to a driving force. What used to be experimental is now essential, reshaping how businesses operate, compete, and grow. At SumatoSoft we’ve leaned into that shift and grown our expertise to help companies put AI to full use.
Awards & recognitions
What’s in SumatoSoft’s AI tech stack?
Here are just a few tools we use for AI software development. Final choice depends on your specific business goals.
Your data never trains public models
Enterprise AI needs a clear architecture. Your proprietary information stays fully under your control at every stage of development and deployment.
VPC-isolated deployment architecture
Your AI runs inside your own cloud, AWS or Azure, walled off with VPC isolation, private subnets, security groups, and IAM policies. The models live inside your security perimeter and reach your internal systems through controlled middleware, never by touching your database directly.
Vector-level role-based access control (RBAC)
We control access at the retrieval layer. Role- and attribute-based rules (RBAC and ABAC) mean a user can only pull the data they’re cleared to see, and we check those permissions before the system retrieves anything or writes a word.
Automated PII redaction pipeline
Before any sensitive data gets indexed or reaches a model, it runs through an automated pipeline that finds and redacts personal information (PII). We use entity recognition, masking, and tokenization to keep protected data out of layers it was never meant to reach.
Private model invocation and secure API mediation
We reach foundation models either through secure API gateways or through private endpoints we deploy for you. Every call is logged and rate-limited, and middleware inside your own infrastructure governs all of it.
Audit logging and access traceability
We log every interaction, each retrieval, each generated answer, and each system call, so you can trace any of them later. The audit trail gives you operational transparency and the records your compliance team needs.
Frequently asked questions
How much does enterprise AI development cost?
Cost depends on scope, data readiness, and how many systems the AI connects to. As a general guide, a proof-of-concept or pilot runs in the low-to-mid five figures. A full production build usually falls between roughly $100,000 and $400,000+, set by model complexity, integrations, and compliance scope. Ongoing monitoring and retraining add about 15–20% of the build cost per year. Our 4–6 week pilot puts a firm cost boundary around the work before you commit to production, including projected cloud and token spend. You can also get an early estimate from our cost calculator.
How long does it take to move from idea to production?
A pilot can be delivered in four to six weeks. A production build follows once the pilot validates feasibility. It usually takes three to nine months, set by how many systems it connects to and how ready your data is. Data readiness is the biggest variable, and we surface it during the pilot rather than mid-build.
Will our proprietary data be used to train public AI models?
No. Enterprise deployments run inside private infrastructure. Your data stays isolated and never trains external foundation models.
Can AI integrate with our legacy systems?
Yes, and it’s most of what we do. We connect models to your existing systems through secure middleware and APIs. The AI reads and writes through a controlled layer instead of touching your database directly. We’ve modernized and integrated legacy platforms for 14+ years, which is what makes the AI layer safe to add.
How do you ensure model quality and reliability?
We evaluate every AI system against defined performance metrics before release, then keep quality steady over time through continuous monitoring, structured testing, and controlled iteration.
More about SumatoSoft
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If you have any questions, email us info@sumatosoft.com
