Assistants and support
Internal assistants, request classification, reply suggestions, and faster handling of recurring cases.
AI for business
AI for business: automation, assistants, and AI features inside products
We implement AI where it creates a concrete business outcome: shorter handling time, better document workflows, smarter decisions, or a useful feature inside the product. No slide-deck hype — from process discovery and pilot, to a working implementation.
The most common AI scenarios
Documents and data
Information extraction, summaries, document workflows, and preparing data for better decisions.
AI inside the product
AI embedded in the app, admin panel, or client workflow — where it truly helps users or the team.
Entry packages
Choose a focused first step before committing to a larger build
Each package is designed to turn an unclear idea, unstable project, or automation opportunity into a concrete scope, decision, and next implementation step. The ranges below are practical starting budgets, not a promise that a larger build will fit inside the package price.
Recommended first step
MVP Kickstart
For founders and teams that need to move from idea to a realistic first release.
Scope workshop, MVP backlog, architecture decisions, risk map, release plan, and implementation estimate.
- Start: focused discovery. Delivery: compact scope sprint.
- Typical budget: PLN 4,000-9,000 net for the discovery package.
Rescue Audit
For products that already exist, but delivery, scope, quality, or ownership is getting unclear.
Technical and product review, key risks, stabilization priorities, and a short recovery roadmap.
- Start: audit of current state. Delivery: prioritized action plan.
- Typical budget: PLN 5,000-12,000 net for the audit.
Integration Sprint
For companies that need systems, APIs, payments, CRM, ERP, or SaaS tools to work together reliably.
One critical flow, integration contract, edge cases, implementation plan, and rollout checklist.
- Start: one process or integration path. Delivery: scoped sprint plan.
- Typical budget: PLN 8,000-20,000 net for the first integration sprint.
AI / Automation Pilot
For teams that want to test AI or automation on a real workflow without turning it into a large program.
Use case diagnosis, data/process review, pilot scope, risk notes, and next-step implementation path.
- Start: practical use case. Delivery: pilot-ready scope.
- Typical budget: PLN 8,000-25,000 net for the pilot.
Is this the final price of the whole project?
No. These are entry packages. They help define scope, risks, architecture, and the next step before estimating a larger build.
Which package should we choose first?
If you are building a new product, start with MVP Kickstart. If you already have a project in motion and need clarity, start with Rescue Audit. For one concrete process, choose Integration Sprint or AI / Automation Pilot.
How we run this kind of implementation
1. Goal and risk
We first define what should improve: handling time, quality of decisions, data flow, or the user experience.
2. Pilot on a real process
We build a small, measurable scope that can be tested quickly on real data and evaluated from a business perspective.
3. Integration and growth
We connect the solution with the app, CRM, documents, or panel and expand only what proves useful in practice.
Outcome
When this kind of implementation makes sense
The best AI projects do not look like technology demos. They give the team less manual work, faster response time, better document handling, and a feature that can be maintained after launch.
FAQ
Questions before starting an AI implementation
Do we need a lot of data to start?
Not always. A sensible pilot can often start with a narrower scope: selected documents, requests, or one fragment of the process.
Does AI need to be a separate product?
No. In many cases, the best outcome comes from AI embedded in the existing panel, workflow, or application instead of a new standalone tool.
How do we know whether the use case has business value?
We look at team time, frequency of repetitive tasks, error risk, and whether the result can be measured after a short pilot.
What is the best place to start?
A small pilot with a clear outcome: faster handling, better classification, less manual work, or better use of data.
Fast first step
Send a short brief. We will come back with scope, risks, and a practical start path.
You do not need a full specification. Describe the product, process, or integration in a few sentences. We will point out what needs clarification, what can be built first, and where the delivery risks are.
What to send
Goal, current state, constraints, and links or materials if they already exist.
What you get back
A concrete next step: scope workshop, MVP Kickstart, Rescue Audit, integration sprint, or a smaller pilot.
Why it helps
Fewer generic calls, faster qualification, and a clearer decision before committing budget.
Have a process or product where AI could create a real outcome?
Describe the use case, data, and constraints in a few sentences. We will come back with a concrete pilot idea, scope, and startup risks.
Contact CHDR