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InnerOS/Projects
PRODUCT · SYSTEMS · APPLIED INTELLIGENCE

Technology at work.
Built from the inside.

Our own software, connected platforms and agents that work with context. Systems shaped by our operations and the work of our teams.

CRM-OSOperationsReportingMulti-brandAssistantsAgent contextIn development
01 / OWN PRODUCT IN DEVELOPMENT

CRM-OS

Customer information connected across channels. An internal product we continue to adapt for public use.

Multichannel · Translation · Context-aware assistant
  1. Channels
  2. Context
  3. Translation
  4. Review

Concept illustration · Prepared translation

The problem

Customer information and conversations are spread across web, WhatsApp, Telegram and email. Teams need to retrieve context and communicate across languages.

What we have built

Connected customer information and conversations, visibility into what was discussed and agreed, message translation and an assistant to retrieve context and prepare communications with human review.

What we have learned

A fuller view of each customer relationship, with less switching between tools and less reliance on remembering which conversation held each detail.

Own product evolving from internal use towards public use. Integrations and permissions are reviewed for each scope.

02 / INTERNAL PILOT IN DEVELOPMENT

Operations Panel

Workflows connecting AI and people to follow processes, understand workloads and support every handoff.

Workflows · Deliverables · Teams

The problem

Assigning tasks is not enough when there are dependencies, reviewers and shift changes.

What we have built

Versioned tasks and deliverables, independent review, time tracking, schedules, roles and configurable workflows.

What we have learned

Visibility into bottlenecks and workloads, with the context each person needs to work and hand off to the next owner.

Built for the group's operations, with an internal pilot. Organisational configuration and integrations continue to evolve.

Real Operations Panel screenshot in Spanish with test data
Test environment, in Spanish. Fictional accounts and data. Select to enlarge.
03 / OUR OWN PRODUCT

PokerLedger

Club report processing and settlement report generation.

Imports · Calculations · Excel

The problem

Data arrives in files with different formats and requires repeated calculations.

What we have built

Reading and mapping columns, commission and rakeback calculation rules, Excel report generation and Telegram workflows.

What we have learned

The technical experience can be applied to reporting and settlements with specific rules, after adaptation.

A specialised poker product. It is not presented as universal accounting software or tax advice.

Try part of the calculation

A working example uses the project's rakeback and action calculation module, adapted for the browser. Fictional input; no additional taxes, payments or production access.

File + rules → report
04 / OUR OWN ECOSYSTEM

PokerDealsAI, EasyPokerApps and EasyAmericanPoker

Specialist acquisition through three portals in one sector, with a shared backoffice.

Multi-brand · Content · Web platform

The problem

Provide a specialist entry point for each product while giving customers shared access to all three.

What we have built

PokerDealsAI, EasyPokerApps and EasyAmericanPoker connected through a shared backoffice, automation, AI layers and agents carrying out customer actions within the ecosystem.

What we have learned

Portals, brand networks and products that share functionality while offering different experiences.

Projects within the group's ecosystem, not three independent external clients.

01 PokerDealsAISpecialist poker rooms
Real public homepage of PokerDealsAI
02 EasyPokerAppsPrivate clubs and apps
Real public homepage of EasyPokerApps
03 EasyAmericanPokerUS-focused poker rooms
Real public homepage of EasyAmericanPoker

Real public homepages · Captured 1 November 2026 · Click to enlarge

05 / OUR OWN ASSISTANT IN DEVELOPMENT

PokerMate

Conversational assistance and context-aware work within the poker ecosystem.

Knowledge · Conversation · Support

The problem

Enquiries require a combination of product knowledge, context and support guidelines.

What we have built

Conversation and knowledge experiences, alongside a support assistance pilot for defined cases.

What we have learned

Specialist assistants and support for the service team, not a generic bot without context.

Capabilities vary by channel and role. The support pilot has a limited scope.

INTERNAL FUNCTIONALITY · AGENT CONTEXT

AI needs to know
what is happening.

We use Telegram Archiver to feed company conversations into our agents’ context. That information is combined with our database, Drive, calendar, schedules and task panel.

This helps them understand where each team member stands and work with operational context. Telegram Archiver is one component of that system.

Functional architecture of the described internal use. This is an explanatory diagram, not a system screenshot.

WORK IN DEVELOPMENT

What we are still building.

Separate from the implementations above: work in development and validation, not products presented as finished.

IN DEVELOPMENT

Agency OS

Product work to organise marketing, content and growth tools. Development is structured around modules and evaluations.

It is not offered here as an autonomous agency or a system that guarantees lead generation.

YOUR NEXT PROJECT

A different sector.
A similar technical challenge.

Tell us about your project You don't need to fit it into a package.
Contact by email; no automatic enquiry delivery.