For Software Agencies
Private AI Development Assistant
Enterprise AI solutions and private AI solutions for your agency. AI coding agents that process documents, onboard developers, understand repositories, automate workflows, and prepare pull requests. Agentic coding on your own infrastructure.
Fixed Fee
Max Timeline
Working System
What You Get
Not a chatbot. An agentic AI solution
Document Processing
Turn scattered company docs into structured, searchable knowledge with source references and freshness tracking.
Developer Onboarding
Role-based onboarding paths with project overviews, setup guides, architecture summaries, and first tasks.
Code Understanding
Search, inspect, and explain code across your repositories. Understand legacy systems without digging through files.
Task Automation
Convert requirements, tickets, and client requests into structured task flows with acceptance criteria and test plans.
AI Coding Agent
Claude Code-style agent that creates plans, applies patches, runs tests, and prepares pull requests — automatically routing each step to the most cost-effective LLM.
Private & Secure
No .env access, no production secrets, no destructive commands. Human approval before every commit and pull request.
Architecture
Six modular technical layers
Model-agnostic, secure, and built to scale. The orchestrator evaluates each task and routes it to the optimal model — using lightweight models for simple lookups and powerful models for complex reasoning, keeping costs low without sacrificing quality.
AI Web App or CLI Agent
Developer-facing interface for commands and interactions
Agent Orchestrator & Model Router
Automatically selects the best LLM per task — fast models for simple queries, powerful models for complex reasoning
Company Knowledge Layer
Document processing, embeddings, project know-how builder
Task Flow Engine
Converts requirements and tickets into development workflows
Safe Development Sandbox
Isolated workspaces, no secrets access, full audit log
Self-Hosted Model Pool
Multiple models (Qwen, DeepSeek, Kimi) served via vLLM or SGLang — the router picks the right one per task
Built-in Workflows
Automate your delivery process
New Feature Workflow
From client request to PR checklist
Bug Fix Workflow
From bug report to regression test
Onboarding Workflow
From new hire to productive developer
PR Review Workflow
From diff to review comments
Project Docs Workflow
From repo to full documentation
Coding Agent Flow
From task to pull request
How It Works
Like Claude Code, but yours
Give the agent a task. It inspects your repository, creates a plan, makes safe code changes, runs tests, fixes failures, and prepares a pull request — all inside a controlled sandbox.
Creates a temporary branch and reads project memory
Inspects repo structure, searches code, reads files
Generates implementation plan and asks for approval
Applies patches, runs tests and linters, fixes errors
Shows final diff, prepares commit or PR after approval
Comparison
Why build your own?
Claude Code & Codex
Fast setup, strong model quality, mature developer experience
Good repo understanding, strong terminal & IDE workflows
Vendor lock-in and ongoing usage costs
Less control over model and workflow customization
Harder to connect with private company knowledge
Private Self-Hosted
RecommendedFull data control on your own infrastructure
Deep integration with docs, tasks, repos, and onboarding
Intelligent model routing — the agent picks the best LLM for each task automatically
Optimize cost at agency scale
Company-specific workflows and coding standards
Infrastructure
GPU costs for 120 people
Realistic pilot assumption: 12-30 active concurrent sessions during busy periods, with queue-based execution for heavier jobs.
GPU infrastructure is a separate ongoing cost paid directly by you to the cloud provider. It is not included in the $9,990 development fee. You choose the tier that fits your team size and workload — and you can scale up or down at any time.
Cost-Controlled Pilot
/month
2x L40S — good for document processing and smaller coding models
Recommended
/month
2x RTX Pro 6000 — better for coding models, more users, better context
High-End Benchmark
/month
4x H100 PCIe — larger model benchmarking, realistic agency workloads
Kimi Heavy Setup
/month
8x H200 — complex agentic tasks, architecture analysis, large refactors
Based on RunPod on-demand pricing. Final cost depends on concurrency, model size, and workload.
Execution Plan
Three months to a working pilot
Month 1 — Foundation
Architecture setup, model runtime, first benchmark, document ingestion pipeline, vector database, first company knowledge structure, security rules.
Month 2 — Workflows & Agent
Company know-how builder, onboarding flows, task breakdown workflows, repo search, file reading, planning mode, safe workspace, patch generation.
Month 3 — Coding Pilot & Handover
File editing, test execution, linter integration, error analysis, test-fix loop, PR preparation, model comparison report, cost recommendation, developer guide, handover.
Scope
What's included in $9,990
✓ Included
× Not Included
Ready to start?
Build your private
AI layer
Book a free 30-minute call. We'll discuss your agency's needs, show you the architecture, and outline the pilot plan.
$9,990 fixed fee • 3-month delivery • Working pilot with production roadmap