01
Generic Agents Miss Repository Reality
Every codebase has its own architecture, patterns, rules, and standards.
PANDORA
PANDORA
PANDORA
PANDORA
Turn Generic AI Coding Agents Into Repository-Aware Engineers
Turn Generic AI Coding Agents Into Repository-Aware Engineers
Turn Generic AI Coding Agents Into Repository-Aware Engineers
Turn Generic AI Coding Agents Into Repository-Aware Engineers
Evaluate, optimize, and tune coding agents against real repository tasks, quality gates, and human reference code.
Evaluate, optimize, and tune coding agents against real repository tasks, quality gates, and human reference code.
Evaluate, optimize, and tune coding agents against real repository tasks, quality gates, and human reference code.
Evaluate, optimize, and tune coding agents against real repository tasks, quality gates, and human reference code.
PRODUCT WALKTHROUGH
Pandora in Motion
Pandora in Motion
Pandora in Motion
A concept interface backed by working technical POCs.
See how Pandora evaluates, optimizes, and tunes AI coding agents for real repositories.
A concept interface backed by working technical POCs.
See how Pandora evaluates, optimizes, and tunes AI coding agents for real repositories.
PANDORA
Evaluation. Optimization.
Intelligence for Real Code.
Test agents. Score runs. Tune systems.
Extract repo-specific intelligence.
01
Build the AI Exam
Tasks, references, rules.
02
Evaluate the Agent
Pandora scores the run.
03
Optimize the System
Improve config, skills, cost.
04
Tune the Model
Turn success into
repo-specific intelligence.
PRODUCT WALKTHROUGH
Pandora in Motion
A concept interface backed by working technical POCs.
See how Pandora evaluates, optimizes, and tunes AI coding agents for real repositories.
PANDORA
Evaluation. Optimization.
Intelligence for Real Code.
Test agents. Score runs. Tune systems.
Extract repo-specific intelligence.
01
Build the AI Exam
Tasks, references, rules.
02
Evaluate the Agent
Pandora scores the run.
03
Optimize the System
Improve config, skills, cost.
04
Tune the Model
Turn success into
repo-specific intelligence.
WHY PANDORA
The Missing Control Layer for AI Coding
The Missing Control Layer for AI Coding
AI coding agents are powerful, but real repositories need more than generated code - they need evaluation, optimization, and trusted feedback loops.
AI coding agents are powerful, but real repositories need more than generated code - they need evaluation, optimization, and trusted feedback loops.
02
Generated Code Needs Validation
Agent output must be checked against repository expectations, tests, and quality gates.
03
Configuration Changes Performance
Skills, tools, context, and provider setup can completely change agent output.
04
Successful Runs Become Intelligence
Measured high-quality runs can become trusted data for repository-specific tuning.
01
Generic Agents Miss Repository Reality
Every codebase has its own architecture, patterns, rules, and standards.
02
Generated Code Needs Validation
Agent output must be checked against repository expectations, tests, and quality gates.
03
Configuration Changes Performance
Skills, tools, context, and provider setup can completely change agent output.
04
Successful Runs Become Intelligence
Measured high-quality runs can become trusted data for repository-specific tuning.
Pandora turns AI coding from guessing into measurable, optimizable, repository-aware engineering.
Pandora turns AI coding from guessing into measurable, optimizable, repository-aware engineering.
WHY PANDORA
The Missing Control Layer for AI Coding
AI coding agents are powerful, but real repositories need more than generated code - they need evaluation, optimization, and trusted feedback loops.
01
Generic Agents Miss Repository Reality
Every codebase has its own architecture, patterns, rules, and standards.
02
Generated Code Needs Validation
Agent output must be checked against repository expectations, tests, and quality gates.
03
Configuration Changes Performance
Skills, tools, context, and provider setup can completely change agent output.
04
Successful Runs Become Intelligence
Measured high-quality runs can become trusted data for repository-specific tuning.
Pandora turns AI coding from guessing into measurable, optimizable, repository-aware engineering.
Explore pandora
One Platform. 3 Areas to Explore
One Platform. 3 Areas to Explore
Explore the method, concept demos and technical proofs across Pandora's 3 core areas
Evaluate
Measure how well an agentic coding platform performs on your repository, standards, and workflows.
1
Build the Exam
Repo-specific coding tasks are defined.
Bug fixes, features, refactors, and repository-specific changes.
2
Add Human Reference
Developers provide the ideal solution.
Reference code shows how the task should be implemented.
3
Run the AI
The AI solves each exam case.
Fresh context, isolated workspace, no hidden reference.
4
Score the Result
Pandora compares AI output to the reference code.
Similarity, structure, compile/pass status, tokens, time, AI judge.
Pandora measures AI performance on your repository - not in general.
Evaluate
Measure how well an agentic coding platform performs on your repository, standards, and workflows.
1
Build the Exam
Repo-specific coding tasks are defined.
Bug fixes, features, refactors, and repository-specific changes.
2
Add Human Reference
Developers provide the ideal solution.
Reference code shows how the task should be implemented.
3
Run the AI
The AI solves each exam case.
Fresh context, isolated workspace, no hidden reference.
4
Score the Result
Pandora compares AI output to the reference code.
Similarity, structure, compile/pass status, tokens, time, AI judge.
Pandora measures AI performance on your repository - not in general.
Explore pandora
One Platform. 3 Areas to Explore
Explore the method, concept demos and technical proofs across Pandora's 3 core areas
Evaluate
Measure how well an agentic coding platform performs on your repository, standards, and workflows.
1
Build the Exam
Repo-specific coding tasks are defined.
Bug fixes, features, refactors, and repository-specific changes.
1/4
Pandora measures AI performance on your repository - not in general.
APPLICABILITY
Built for Any Repository
Built for Any Repository
Pandora is designed around a platform-agnostic direction for repositories, coding agents and engineering workflows.
Any codebase
Connect any repository, in any language.
Any coding agent
Works with the agents your team already trusts.
Any stack
Fits your tech stack and architecture.
Any team
Built for individuals, teams and organizations
Any codebase
Connect any repository, in any language.
Any coding agent
Works with the agents your team already trusts.
Any stack
Fits your tech stack and architecture.
Any team
Built for individuals, teams and organizations
Any codebase
Connect any repository, in any language.
Any coding agent
Works with the agents your team already trusts.
Any stack
Fits your tech stack and architecture.
Any team
Built for individuals, teams and organizations
Works where you work
Frontend
API
Backend
Data
Java
Python
TypeScript
CI/CD
Monorepo
Test Automation
Works where you work
Frontend
API
Backend
Data
Java
Python
TypeScript
CI/CD
Monorepo
Test Automation
APPLICABILITY
Built for Any Repository
Pandora is designed around a platform-agnostic direction for repositories, coding agents and engineering workflows.
Any codebase
Connect any repository, in any language.
Any coding agent
Works with the agents your team already trusts.
Any stack
Fits your tech stack and architecture.
Any team
Built for individuals, teams and organizations
Works where you work
Frontend
API
Backend
Data
Java
Python
TypeScript
CI/CD
Monorepo
Test Automation
interactiive MOCK
Explore the Concept Interface
Explore the Concept Interface
Use the interactive concept interface to explore Pandora’s control room. Technical flows are demonstrated separately through working POCs.
Best viewed on desktop or large tablet.
Explore on Desktop
This interactive mock is built for a full workspace view. Open it on desktop to experience it properly.
interactiive MOCK
Explore the Concept Interface
Use the interactive concept interface to explore Pandora’s control room. Technical flows are demonstrated separately through working POCs.
Best viewed on desktop or large tablet.
TRANSFORMATION
From AI-Assisted to Autonomous Engineering
From AI-Assisted to Autonomous Engineering
AI agents can already generate and modify code. The next challenge is making their work measurable, optimizable, and trusted inside real repositories.
PAST
Human Coding
Developers manually write and validate code.
CURRENT
AI-Assisted Coding
Agents help generate and modify code faster.
GOAL
Fully Autonomous Coding
Measured autonomous execution.
PANDORA
Repository Control Layer
Evaluate • Optimize • Tune
Transition 01
Enabled by agentic
coding platforms
Human-led work becomes AI-assisted execution.
Transition 02
Enabled by Pandora
Repository-specific evaluation, optimization, and tuning.
PAST
Human Coding
Developers manually write and validate code.
CURRENT
AI-Assisted Coding
Agents help generate and modify code faster.
GOAL
Fully Autonomous Coding
Measured autonomous execution.
PANDORA
Repository Control Layer
Evaluate • Optimize • Tune
Transition 01
Enabled by agentic
coding platforms
Human-led work becomes AI-assisted execution.
Transition 02
Enabled by Pandora
Repository-specific evaluation, optimization, and tuning.
PAST
Human Coding
Developers manually write and validate code.
CURRENT
AI-Assisted Coding
Agents help generate and modify code faster.
GOAL
Fully Autonomous Coding
Measured autonomous execution.
PANDORA
Repository Control Layer
Evaluate • Optimize • Tune
Transition 01
Enabled by agentic
coding platforms
Human-led work becomes AI-assisted execution.
Transition 02
Enabled by Pandora
Repository-specific evaluation, optimization, and tuning.
Pandora is not another coding agent - it is the control layer that helps existing agents become repository-aware and eventually autonomous.
Pandora is not another coding agent - it is the control layer that helps existing agents become repository-aware and eventually autonomous.
TRANSFORMATION
From AI-Assisted to Autonomous Engineering
AI agents can already generate and modify code. The next challenge is making their work measurable, optimizable, and trusted inside real repositories.
PAST
Human Coding
Developers manually write and validate code.
Transition 01
Enabled by agentic
coding platforms
Human-led work becomes AI-assisted execution.
CURRENT
AI-Assisted Coding
Agents help generate and modify code faster.
Transition 02
Enabled by Pandora
Repository-specific evaluation, optimization, and tuning.
PANDORA
Repository Control Layer
Evaluate • Optimize • Tune
GOAL
Fully Autonomous Coding
Measured autonomous execution.
Pandora is not another coding agent - it is the control layer that helps existing agents become repository-aware and eventually autonomous.
NEXT STEP
Talk to Us
Explore Pandora’s concept, technical proofs, product direction, and the path toward repository-aware AI engineering.
If this direction is relevant to you, continue to the contact page and start a conversation.
Concept Direction
Technical Proofs
Repository Workflows
From experiments to repository-aware AI engineering.
NEXT STEP
Talk to Us
Explore Pandora’s concept, technical proofs, product direction, and the path toward repository-aware AI engineering.
If this direction is relevant to you, continue to the contact page and start a conversation.
Concept Direction
Technical Proofs
Repository Workflows
From experiments to repository-aware AI engineering.