The problem
Code, requirements, discussions and checks are scattered across tools. Teams spend time rebuilding context, handing off decisions and verifying outcomes at each stage.
A workspace for engineering teams
CodeGryphon combines project context, task execution and result verification across the software development lifecycle.
Working productDesktop · Web · TelegramBuilt for engineering teams
The full workflow, in project context
CodeGryphon connects tasks, team knowledge, tools and result verification. It is evolving from individual assignments to recurring engineering processes.
Our approach
Shared project rules and memory, personal work chats, Desktop execution and access through Web and Telegram. Control Center and Pulse connect daily tasks with project health.
MARKET
Why this market
Working with models is becoming part of everyday development. Our focus is teams that need shared context, execution control and repeatable results.
Initial target segment
Small product teams, development studios and technical leads maintaining existing codebases and several parallel projects.
84%
of survey respondents use or plan to use AI in development
51%
of professional developers in the survey use AI daily
The product foundations
Team-wide context
Knowledge, rules, focuses and results stay with the project and are available according to roles.
Execution and control
Code, commands, the browser and integrations form one workflow with results that can be verified.
Task-informed model selection
Our SDLC benchmark compares quality, time and usage to guide model selection for Gryphon modes.
Business model
Usage revenue
Glyphs account for product usage. Users top up their balance and choose a mode for the task.
Organizations
Deployment, infrastructure requirements and support are discussed through team pilots.
Execution economics
Model selection and context management help control task usage; the benchmark measures quality.
What exists today
The product foundation is available to explore and demonstrate.
Three ways to work
Desktop, Web and Telegram share projects and an account.
Team workflows
Context, roles, focuses, Control Center and Project Pulse.
Quality measurement
Benchmark methodology and model comparison across three metrics.
Development history
Completed milestones, current work and future directions.
The next stage of growth
Developing recurring use within teams: from the first task to regular workflows and multiple projects.
Acquisition
Engineering task demonstrations, professional communities, partnerships and team pilots.
Retention
Schedules, shared knowledge and repeatable working methods. Measuring the workflows that bring teams back.
Economics
Measure the cost of accepted outcomes, usage and cohort retention. Select models by quality and resource use.
Technology development
Two planned directions: our own model for engineering tasks and predictive analysis of project problems.
Gryphon.Model
Training and developing our own model, evaluated on our SDLC benchmark. The aim is to adapt it to Gryphon tasks and tools and manage the balance between result quality, execution time and cost.
ML forecasting of project problems
A forecasting mechanism based on project history and trends. The aim is to identify quality, delivery and technical debt risks early and help teams prioritize what to investigate through Project Pulse and Control Center.
Leading the product forward
Kirill Ivanov
Product Lead & CTO
Sergey Zachesov
Architect
Yulia Malovitsa
Marketing & Communications
Investment and strategic partnerships
We welcome conversations about product development, market expansion and partnerships. The presentation, financial model and potential investment terms are available through a direct conversation with the team.