One Convergence Enterprise Agent Network - Where 4 specialized AI agents collaborate to architect, code, test, and deploy your software automatically.
Traditional software development is slow, expensive, and repetitive. Your team deserves better.
Weeks spent on boilerplate code, repetitive tasks, and manual testing instead of building features that matter.
$20-50 per developer per month for AI coding assistants. Costs spiral with team growth.
Hours of configuration, API keys, environment setup for each developer before they can start coding.
No visibility into what teammates are building. Knowledge silos. Merge conflicts. Duplicated work.
Code quality varies by developer. No standardized patterns. Technical debt accumulates.
No insights into team productivity, bottlenecks, or project health until it's too late.
Four specialized AI agents that work together like a real development team - but 10x faster.
Designs system architecture, database schemas, and API structures based on requirements.
Writes production-ready code following best practices and your team's patterns.
Creates comprehensive tests and validates code quality automatically.
Handles deployment, CI/CD pipelines, and infrastructure management.
Everything you need for modern software development, powered by AI.
AI agents remember your preferences, past decisions, and successful patterns. Every project makes them smarter.
See what teammates are building live. Activity feed, presence tracking, and time-travel replay of coding sessions.
Share and discover proven development patterns. One-click installation of battle-tested solutions.
Unlock achievements and advanced features as you build. Track team progress and celebrate wins.
AI-powered insights into team performance, bottleneck predictions, and project health metrics.
Replay any coding session. See exactly how code evolved. Perfect for code reviews and learning.
Branch protection, PR workflows, automated CI/CD, and centralized version control.
One API key for your entire team. No per-seat licensing. Scale without worrying about costs.
Deep dive into how OCEAN solves real engineering challenges with AI-powered automation.
Traditional AI coding tools like Copilot suffer from stateless interactions. Every conversation starts from scratch, losing architectural decisions, coding patterns, and project context. This leads to inconsistent code suggestions and repeated explanations.
OCEAN implements a multi-agent system where each agent (Architect, Developer, QA, DevOps) maintains persistent memory using Letta's memory management system. Agents remember:
// Architect Agent with Memory
class ArchitectAgent extends LettaEnhancedAgent {
async designSystem(requirements: string) {
// Retrieve past architectural decisions
const memory = await this.getLettaMemory();
const pastPatterns = memory.patterns || [];
// Design with context awareness
const design = await this.callClaude({
systemPrompt: this.getPersona(),
context: {
requirements,
pastPatterns,
techStack: memory.techStack,
scalabilityNeeds: this.assessScalability(requirements)
}
});
// Store decision for future reference
await this.storeLettaMemory({
decision: design,
timestamp: new Date(),
reasoning: design.reasoning
});
return design;
}
}
// WebSocket-based Real-Time Presence
class PresenceService {
private io: Server;
private redis: Redis;
async trackPresence(userId: string, data: PresenceData) {
// Store in Redis with TTL
await this.redis.setex(
`presence:${userId}`,
30, // 30 second heartbeat
JSON.stringify({
...data,
lastSeen: Date.now(),
currentFile: data.file,
cursorPosition: data.cursor
})
);
// Broadcast to team
this.io.to(data.teamId).emit('presence:update', {
userId,
action: data.action,
file: data.file,
cursor: data.cursor
});
}
async getCursors(teamId: string) {
const keys = await this.redis.keys(`presence:*`);
const cursors = await Promise.all(
keys.map(k => this.redis.get(k))
);
return cursors.filter(c => c.teamId === teamId);
}
}
GitHub-style async collaboration creates delays: push โ wait for review โ address comments โ repeat. Average PR cycle time: 2-3 days. Developers context-switch constantly, losing flow state.
OCEAN implements Google Docs-style real-time collaboration for code:
Developers spend 60-70% of time on repetitive tasks: CRUD operations, API endpoints, database migrations, test boilerplate, Docker configs. This is undifferentiated heavy lifting that doesn't create business value.
OCEAN's Developer Agent generates production-ready code across the entire stack:
// Generated API Route with Type Safety
import { NextRequest, NextResponse } from 'next/server';
import { z } from 'zod';
import { prisma } from '@/lib/db';
const createUserSchema = z.object({
email: z.string().email(),
name: z.string().min(1).max(255),
role: z.enum(['admin', 'user'])
});
export async function POST(req: NextRequest) {
try {
const body = await req.json();
const validated = createUserSchema.parse(body);
// Check for existing user
const existing = await prisma.user.findUnique({
where: { email: validated.email }
});
if (existing) {
return NextResponse.json(
{ error: 'User already exists' },
{ status: 409 }
);
}
// Create user with transaction
const user = await prisma.user.create({
data: validated,
select: {
id: true,
email: true,
name: true,
role: true,
createdAt: true
}
});
return NextResponse.json(user, { status: 201 });
} catch (error) {
if (error instanceof z.ZodError) {
return NextResponse.json(
{ error: 'Validation failed', details: error.errors },
{ status: 400 }
);
}
return NextResponse.json(
{ error: 'Internal server error' },
{ status: 500 }
);
}
}
// Automated Branch Protection & PR Workflow
class GitManagementService {
async setupRepository(repoPath: string) {
// Initialize bare repo
await git.init(repoPath, { bare: true });
// Configure branch protection
await this.setBranchProtection('main', {
requirePullRequest: true,
requiredReviewers: 1,
requireStatusChecks: true,
requiredChecks: [
'ci/tests',
'ci/lint',
'ci/type-check',
'security/scan'
],
enforceAdmins: false,
restrictPushes: true
});
// Set up webhooks for CI/CD
await this.createWebhook({
events: ['push', 'pull_request'],
url: `${process.env.CI_URL}/webhook`,
secret: process.env.WEBHOOK_SECRET
});
// Configure merge strategies
await this.setMergeStrategy({
allowSquash: true,
allowMerge: false,
allowRebase: true,
deleteBranchOnMerge: true
});
}
async onPushToMain(commit: Commit) {
// Trigger deployment pipeline
await this.triggerPipeline({
stage: 'production',
commit: commit.sha,
runTests: true,
runSecurityScan: true,
deployTarget: 'production'
});
}
}
As teams grow, Git becomes chaotic: inconsistent branch naming, unprotected main branches, manual deployments, no code review enforcement. Result: production bugs, merge conflicts, deployment delays.
OCEAN enforces Git best practices automatically:
/projects/central-repo/projects-main.gitTraditional project management is reactive: you only know about bottlenecks when deadlines slip, quality issues when bugs hit production, team burnout when people quit. By then, it's too late.
OCEAN analyzes team metrics in real-time to predict problems before they happen:
// Predictive Analytics Engine
class AnalyticsEngine {
async predictBottlenecks(teamId: string) {
// Gather historical data
const commits = await this.getCommitHistory(teamId, 30);
const prs = await this.getPRMetrics(teamId, 30);
const velocity = this.calculateVelocity(commits);
// Analyze current sprint
const activeTasks = await this.getActiveTasks(teamId);
const predictions = activeTasks.map(task => {
const complexity = this.assessComplexity(task);
const assigneeVelocity = velocity[task.assignee];
const timeRemaining = task.deadline - Date.now();
// Predict completion probability
const completionProb = this.predictCompletion({
complexity,
velocity: assigneeVelocity,
timeRemaining,
historicalData: commits
});
return {
taskId: task.id,
completionProbability: completionProb,
isAtRisk: completionProb < 0.7,
recommendedAction: completionProb < 0.7
? 'Reassign or extend deadline'
: 'On track'
};
});
return predictions.filter(p => p.isAtRisk);
}
private predictCompletion(params: PredictionParams): number {
// ML model for completion prediction
const features = [
params.complexity / 10,
params.velocity,
params.timeRemaining / (24 * 60 * 60 * 1000)
];
return this.mlModel.predict(features);
}
}
// Pattern Installation & Dependency Resolution
class PatternInstaller {
async installPattern(patternId: string, projectPath: string) {
const pattern = await this.fetchPattern(patternId);
// Resolve dependencies
const deps = await this.resolveDependencies(pattern);
for (const dep of deps) {
if (!await this.isInstalled(dep)) {
await this.installDependency(dep);
}
}
// Generate code from pattern
const files = await this.generateFiles(pattern, {
projectPath,
config: await this.getProjectConfig(projectPath)
});
// Write files
for (const file of files) {
await fs.writeFile(
path.join(projectPath, file.path),
file.content
);
}
// Activate MCP if pattern includes one
if (pattern.mcp) {
await this.activateMCP(pattern.mcp);
}
// Log usage for analytics
await this.logInstallation({
patternId,
userId: this.userId,
timestamp: Date.now()
});
return {
filesCreated: files.length,
dependencies: deps.length,
mcpActivated: !!pattern.mcp
};
}
}
Every team builds the same things over and over: authentication, pagination, file uploads, email sending, payment processing. Each implementation has subtle bugs and security issues. No knowledge sharing across teams.
OCEAN's Pattern Marketplace is like npm for architectural patterns:
Debugging is guesswork: developers describe bugs verbally, reviewers can't see the actual coding process, junior devs struggle to understand how senior devs solve problems. Code review is static - you see the final diff, not the thought process.
OCEAN records every coding session with sub-100KB compression:
// Session Recorder with Compression
class SessionRecorder {
private events: RecordingEvent[] = [];
private lastSnapshot: string = '';
recordEvent(event: CodeChangeEvent) {
// Store only diff from last state
const diff = this.computeDiff(
this.lastSnapshot,
event.content
);
this.events.push({
type: event.type,
timestamp: Date.now(),
diff: diff, // Much smaller than full content
metadata: {
file: event.file,
cursor: event.cursor,
aiSuggestion: event.aiSuggestion
}
});
this.lastSnapshot = event.content;
}
async stopRecording() {
// Compress event stream
const compressed = await brotli.compress(
JSON.stringify(this.events)
);
// Store in database
await db.sessionRecordings.create({
userId: this.userId,
projectId: this.projectId,
duration: this.getDuration(),
events: compressed, // ~100KB for 1hr session
highlights: this.extractHighlights(),
createdAt: new Date()
});
return {
size: compressed.length,
eventCount: this.events.length,
compressionRatio: this.getCompressionRatio()
};
}
}
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