First we understand the business. Then we build the technology.

Business analysis · AI · Software · Integration · Support

We run a pre-project company audit, digitize processes, find points of growth, and create technology with AI and the OBS Pulse SaaS platform used under a licence agreement.

−32%

manual load on the first process taken into production

6–12 weeks

from pre-project company audit to a production slice with integrations

39%

of companies already use AI assistants (SberAnalytics, 2025)

Your business is the starting point

We do not offer technology before we understand the task. First we study how the company earns money, where losses appear, which processes slow growth, and how the existing IT landscape is arranged. Then we draw a map of change and choose the technologies that have economic sense.

About the pre-project company audit

From a business problem to a working system

  1. 01

    Diagnosis

    We study the business model, processes, organisation, data, and the IT systems already in place.

  2. 02

    Digitization

    We build a digital model of the key processes and how they connect inside the company.

  3. 03

    Analysis

    We find bottlenecks, manual work, lost time, duplication, and points of growth.

  4. 04

    Strategy

    We decide which changes will produce the greatest effect — and in which order to implement them.

  5. 05

    Build

    We create the digital products, AI services, automation, and internal systems the plan requires.

  6. 06

    Integration

    We connect new solutions to CRM, ERP, BI, APIs, and the rest of the client’s stack.

  7. 07

    Support

    We stay after launch: we operate, measure the result, and keep developing the system.

The OBS Pulse SaaS platform shortens the path from analysis to build

Inside the company we use the OBS Pulse SaaS platform under a licence agreement with the rights holder. It combines business analysis, work with data, and AI tools for design and development. That lets us turn pre-project company audit findings into concrete solutions faster — from hypotheses and prototypes to working digital products.

Faster

AI helps analysts and engineers cut routine work and prepare solutions sooner.

More precise

Business-analysis results become the basis for design — not a separate document that dies in a folder.

More systemic

Analysis, product management, and engineering work in one loop.

About the platform

We choose technology by the task, not by fashion

For a mid-market company the question is not only what a technology can do, but whether it is available, stable, secure, integrable, and supportable over years. We design durable solutions around the IT landscape, security requirements, and infrastructure of the market you operate in.

  • AI and cloud platforms

    Selected for the market, the data policy, and the workload.

  • Corporate systems

    CRM, ERP, and the systems of record you already trust.

  • API integrations

    New capability sits inside existing flows, not beside them.

  • On-premise / cloud

    Hosting follows policy, latency, and cost — not a default slogan.

  • Hybrid architecture

    When one contour cannot hold the whole operating model.

One team from diagnosis to operations

  • Business analysts

    understand the business.

  • Product managers

    turn problems into solutions.

  • AI specialists

    decide where AI is actually needed.

  • Software engineers

    build the system.

  • Integration engineers

    connect it to the existing infrastructure.

  • Support

    stay after launch.

The task does not stop at a specification

We do not hand a business problem to an engineer as a technical brief and walk away. Analysts and the product team work with developers for the whole project. That is how a diagnosis becomes a system that actually runs.

If you are still at the idea

Idea → business model → hypothesis tests → MVP → launch. We do not build an MVP for its own sake. First we check what the market must prove.

Talk about the idea

Questions companies actually ask

How much does a pre-project company audit cost?

A fixed-scope diagnostic typically starts from USD 8,000 and takes two to three weeks. The number moves with the number of systems, sites, and process owners involved. We quote the pre-project company audit before we quote the build.

What is included in a pre-project company audit?

A map of how the company actually earns money; the processes, data, organisation, and IT systems behind it; bottlenecks and growth points; and a sequenced change plan. You leave with a document you can take in-house — not a slide that only we can interpret.

Do we have to replace our CRM or ERP?

Usually no. We start from the systems you already run. Replacing a system of record is a last resort, not a default. The typical job is to connect new capability to what already holds the truth.

Can AI be integrated with our existing systems?

Yes, when the process, data, and access rules allow it. We connect to CRM, ERP, BI, telephony, document stores, and APIs. If a system cannot be integrated safely, we say so in the pre-project company audit instead of forcing a side chatbot.

Which AI solutions fit mid-market companies?

The ones that change a measured workflow: assistants and agents in sales, support, documents, HR, finance, and internal knowledge; automation of repetitive hand-offs; analytics that operators actually use. Not a model for every department on day one.

Can we use local or international AI platforms?

We choose the stack from the task: availability, security, data residency, integrability, and long-term support in your market. That can mean local platforms, international models, on-premise, cloud, or a hybrid — not a fashion choice.

Where is the data stored?

Where the engagement specifies: your tenant, a regional cloud, or a hybrid. We do not move production data into a demo sandbox and leave it there. Residency and access control are part of the design, not an afterthought.

Can the solution run in a regional cloud?

Yes. We design for the cloud, infrastructure, and security rules of the market you operate in. If the requirement is a specific provider or region, that constraint is in the architecture from the pre-project company audit.

Can we use our own infrastructure?

Yes. On-premise and hybrid deployments are a normal option when policy, latency, or cost require it. The product still has to connect to the systems of record — hosting is a decision, not the whole design.

How long does an AI implementation take?

A pilot on one process is typically weeks, not quarters. A production slice with integrations is often 6–12 weeks after the pre-project company audit. Scaling to more processes follows measured results, not a big-bang programme.

How is ROI calculated?

From a baseline taken in the pre-project company audit: time per task, cost per case, error rate, cycle time, or revenue leakage. We estimate effect on that metric before the build and measure it after go-live. If the case is weak, we recommend not to build.

Can we start with a pilot?

That is the default. Pre-project company audit → use case → business case → pilot → integration → scale. A pilot is a working slice in the live process, not a disconnected prototype.

Do you develop SaaS products?

Yes. We build customer-facing and internal platforms when the business model needs a product, not only an automation. Internally we use the OBS Pulse SaaS platform under a licence agreement — without handing the full architecture to the market.

Do you work with international clients?

Yes. The English site is for international mid-market companies and founders. We analyse how the business works, then design and build what the operating model actually needs.

Do you help create an MVP?

Yes — after we test the business hypothesis. We do not build an MVP for its own sake. First we decide what must be proven on the market; only then we build the smallest product that can prove it.

Not sure where your business needs AI?

That is normal. We will not start with a tool. We will start with an analysis of your business.