Web apps and dashboards for daily operations
We build working interfaces for teams that have outgrown spreadsheets, chats, and scattered admin screens: internal tools, client portals, dashboards, moderation panels, and operational workspaces.
— 01 / TASKS
What we can build
A good operational interface is not a showroom. It helps people understand status, find the right record, fix a problem, and make the next decision faster.
Operational dashboards
We bring statuses, metrics, filters, and exceptions into one screen for daily control.
The team can see where work is stuck without assembling reports by hand.
Admin panels
We design roles, lists, record views, bulk actions, change logs, and safe confirmation flows.
Internal work becomes manageable without giving people direct database access.
Client portals
We give clients a clear place for requests, documents, statuses, payments, messages, or reports.
There are fewer follow-up chats and more transparency for both sides.
Data-heavy interfaces
We build tables, filters, comparisons, charts, and exports when data needs to be worked with, not just viewed.
Complex information becomes usable, not merely stored somewhere.
Support workspaces
We create an operator view for tickets, history, suggestions, templates, escalations, and quality checks.
Operators answer faster, and managers can see what causes delays or mistakes.
AI-ready workflows
We add places where AI can search, suggest a draft, or flag risk while a person keeps control of the action.
AI becomes part of the workflow instead of a separate experiment window.
— 02 / FIT
When a custom web tool is worth it
Custom development starts to make sense when a standard CRM, BI tool, or no-code setup slows the team down: too many workarounds, access rules, unusual statuses, and data sources that do not quite meet.
The team runs on spreadsheets, but the data has become too important for manual handling.
CRM, documents, payments, inventory, support, analytics, or an internal API need to work together.
Different roles need different screens, permissions, actions, and responsibility boundaries.
The interface has to survive daily use: errors, search, filters, logs, empty states, and disputed cases.
— 03 / PROCESS
What the build includes
Task and data audit
We inspect real tickets, documents, spreadsheets, and access rules.
Scenario design
We define where AI replies, where it acts, and where a human stays in the loop.
Prototype
We build a working first version against samples from your actual workflow.
Integrations
We connect CRM, messengers, databases, documents, or internal APIs.
Testing
We test on real dialogs, questions, and files, not just friendly demo prompts.
Launch
We put the system into work with clear roles, logs, and control points.
Quality monitoring
We review wrong answers, edge cases, escalations, and user behavior.
Support and iteration
We improve scenarios after launch, once real usage starts showing the truth.
— 04 / WORK
Related interface work
These projects are close in shape: lots of data, user roles, internal operations, admin surfaces, and interfaces over complex logic.
AI Assistant · Internal Knowledge · Enterprise
Olzhas — Magnum Knowledge Base
An internal AI assistant for Magnum employees: ask a question in plain language, get an answer pulled from the company knowledge base.
Internal Comms · LMS Integration · EnterpriseMagnum Notifications & LMS
Internal notification platform for Magnum: training reminders pulled from the LMS, plus targeted corporate broadcasts to specific stores, departments and offices.
AI Infrastructure · Telegram Mini-App · EventsKaizen Club · TheNext
AI infrastructure for a three-day business summit in Abu Dhabi — one Telegram Mini-App that carries every attendee from the first click on a ticket to materials after.
Operations · Supplier OnboardingCompass
A supplier onboarding workflow for Compass, focused on moving operational steps out of scattered manual coordination.
— 05 / INTEGRATIONS
Integrations
We usually connect databases, CRM, documents, payments, messengers, BI sources, internal APIs, and AI services where they genuinely help the operator.
CRMWhatsAppTelegramGoogle SheetsNotionAirtable1CBitrix24amoCRMPostgreSQLSupabaseOpenAIAnthropiccustom APIvector databases
— 06 / DATA
Security and data handling
We design the architecture around your requirements: roles, access rules, action logs, source restrictions, and answer checks.
Not every data source has to be sent to a public model. Some logic can stay inside your infrastructure.
Document access and agent actions can be restricted by role.
For important decisions, we add human-in-the-loop review: AI prepares the answer or draft, a person confirms it.
Test environments stay separate from production, so scenarios and prompts can be checked safely.
— 07 / TIMELINE
Timeline and working format
Fast audit
2-3 business days when sample data and a process owner are available.
Prototype
1-2 weeks for a narrow scenario with a limited integration set.
MVP
3-6 weeks when the system needs real integrations and team access.
Production
Timeline depends on integrations, data quality, and security requirements.
— 08 / PRICING
Pricing
Pricing depends on integrations, data quality, access roles, testing scope, and infrastructure requirements. Each stage is paid separately.
Discovery
A paid review of the task, data, risks, and first sensible scope.
Prototype
We test the scenario on a small data set before debating it in theory.
MVP
We build a working version with UI, integrations, and basic quality control.
Production system
We harden the system for access control, logs, operations, and support.
Support
We monitor quality, fix issues, and add new scenarios after launch.
— 09 / azamat.ai
Why azamat.ai
We design from the work itself: statuses, roles, errors, queues, and the next action.
We can connect frontend, backend, databases, integrations, AI, and access control.
We are comfortable with dense data-heavy screens where speed matters more than landing-page polish.
The founder stays involved in architecture and hard product calls.
Our work covers HR tools, knowledge bases, notifications, events, education, and client portals.
— 10 / FAQ
FAQ
Yes. The right first step is often one screen for the process with the most manual pain: statuses, errors, queue, documents, or requests.
We do both interface and engineering. These projects usually need UX, frontend, backend, integrations, access roles, testing, and a careful launch.
Yes, if there is an API, export, webhook, or safe direct access. During discovery we check constraints, data quality, and permissions.
BI is usually for looking at metrics. An operational web tool also lets people act: change a status, assign an owner, review a record, message a client, or start the next step.
Yes. AI can search documents, draft replies, explain anomalies, or help an operator. Important actions should still require human confirmation.
Tell us what you're building.
Start with a few detailsWe reply within one business day. Then Azamat joins every first call personally, so you get an honest scope, budget, and fit from the person responsible for delivery.