Sanciti AI Agents Hub
Most teams stitch together five or six disconnected tools and call it a pipeline. Sanciti AI replaces that patchwork with four enterprise AI SDLC agents working as one coordinated system. Each AI coding agent owns a phase of delivery and passes full context to the next, so requirements, code, validation, and deployment stay connected from start to finish.
Specialized Agents
Automated SDLC Coverage
Core Orchestration Engines
Effort & Cost Reduction
The Agentic AI Pipeline
Requirements flow into code. Code flows into validation. Validation flows into production bundles. Every handoff carries full context, so nothing gets lost between phases.
Understand
Build
Validate
Ship
Phase 1: Understand
Before a single line of code gets written, someone needs to define what “done” actually looks like. RGEN handles that. It pulls from source code, design documents, meeting transcripts, and stakeholder conversations, then structures everything into requirements that engineering teams can actually execute against.
Traditional requirements gathering takes weeks of workshops and produces documents nobody reads. RGEN as an AI coding agent produces eight distinct output types in minutes, each traceable back to source material. These are agentic GEN AI agents applied to the hardest part of delivery: understanding what to build.
8 Output Types:
INPUTS:
OUTPUTS:
Phase 2: Build
CodeGen picks up where RGEN leaves off. It takes structured requirements, combines them with your application metadata and tech stack configuration, and generates complete, secure modules through an iterative write-evaluate-refine loop. Not fragments. Not suggestions. Production-grade code aligned to your architecture, delivered at up to 90% completeness on the first pass.
Your team reviews and refines what CodeGen produces rather than writing from scratch. Security policies are enforced by default, OWASP and NIST patterns are embedded in generation, and every output carries its requirements lineage. That is what separates an enterprise AI coding agent and AI code agent from a simple autocomplete tool.
How CodeGen Achieves 90% Completeness
INPUTS:
OUTPUTS:
Phase 3: Validate
Code without validation is a liability. TestAI, the autonomous AI agent in the pipeline, generates test cases from what CodeGen produces, executes them, analyzes failures, and self-heals broken scripts when the underlying code changes. Brittle suites and manual regression runs become problems your team no longer manages.
Six capabilities run in parallel: functional, integration, regression, performance, and security validation execute as a coordinated suite. The output is audit-grade evidence showing exactly what was covered, what passed, and what needs attention before release.
6 Testing Capabilities
INPUTS:
OUTPUTS:
Phase 4: Ship
Validated code still needs packaging, configuration, and documentation before it reaches production. Deploy, the autonomous AI agent handling the final phase, generates containerized delivery bundles, deployment scripts, infrastructure configurations, and release documentation so your operations team ships with confidence, not guesswork.
What ships is not a zip file. It is a production-ready bundle: deployment manifests, rollback procedures, environment configurations, and compliance documentation. Every artifact traces back through TestAI, CodeGen, and RGEN to the original requirement. Intent to production, fully auditable.
Delivery Bundle Contents
INPUTS:
OUTPUTS:
Agentic AI Architecture
The agents do not operate in isolation. Five shared engines sit underneath, coordinating behavior, managing context flow, enforcing governance, and producing the audit trail that enterprise procurement and compliance teams expect.
Parses and indexes source code, documents, and data sources into a unified knowledge graph shared across the pipeline.
Analyzes inputs to understand what needs to happen by classifying requirements, identifying dependencies, and resolving ambiguity.
Routes work between agents, manages pipeline sequencing, and ensures context flows forward without loss or corruption.
Manages agent lifecycles, enforces quality gates, handles retries and escalations, and coordinates parallel execution.
Logs every decision, transformation, and output. Generates compliance evidence packs so you can trace any artifact back to its origin.
LLM-Agnostic by Design
The orchestration layer works with any foundation model including Claude, GPT, Llama, Gemini, or Mistral. Swap agentic models per agent or per task without changing your pipeline. No vendor lock-in.
Enterprise Integrations
Sanciti AI’s agentic GEN AI agents plug directly into the tools your engineering and operations teams already use. No migration project. No new workflows to learn.
JIRA
GitHub
GitLab
SharePoint
AWS S3
MinIO
Confluence
Slack
Positioning
Sanciti AI vs. AI Coding Assistants
GitHub Copilot and Cursor make individual developers faster. Sanciti AI operates at a different level: governing the entire delivery lifecycle as an auditable, enterprise-grade pipeline where requirements, code, validation, and deployment stay connected.
AI Coding Assistants (Copilot, Cursor):
Sanciti AI (Agentic AI for SDLC Platform):
Enterprise-grade compliance and certifications
V2Soft: 28 years of enterprise delivery · 17 global locations · Single-tenant deployment · Private VPC (AWS / Azure)
Walk through a live demonstration. See RGEN, CodeGen, TestAI, and Deploy working together on a real codebase, with governance, security scoring, and traceability visible at every step.
Full-service framework including:
Generates Requirements, Use cases, from code base.
Generates Automation and Performance scripts.
Code vulnerability assessment & Mitigation.
Production support & maintenance, Ticket analysis & reporting, Log monitoring analysis & reporting.
AI-Powered Legacy Modernization That
Accelerates, Secures, and Scales
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See how Sanciti Al can transform your App Dev & Testing
SancitiAl is the leading generative Al framework that incorporates code generation, testing automation, document generation, reverse engineering, with flexibility and scalability.
This leading Gen-Al framework is smarter, faster and more agile than competitors.
Why teams choose SancitiAl:
