FREQUENTLY ASKED QUESTIONS
Sanciti AI is an agentic AI platform for enterprise software delivery, built by V2Soft in Bloomfield Hills, Michigan. Find answers on how the platform and its AI agents work, how it is deployed and secured, which LLMs it supports, how pricing works and how to get started.
Sanciti AI is an agentic AI platform for enterprise software development and legacy modernization, built by V2Soft and headquartered in Bloomfield Hills, Michigan.
Sanciti AI LLC is a V2Soft company. V2Soft is an AI solutions company since 2016 with 28 years of enterprise delivery experience and teams in 17 locations across 6 countries.
Yes. Sanciti AI LLC is based in Bloomfield Hills, Michigan, with delivery support from the US, Canada, Mexico and India.
Mostly big enterprises: financial services, insurance, healthcare, automotive, manufacturing, government, energy, retail. The person who typically reaches out is a CIO, CTO, or head of engineering.
Sanciti AI is built for enterprise teams, with paid licenses starting at 50 users. Small teams that only need code completion are better served by a coding assistant.
Call +1 248-904-1737, email info@sanciti.ai, or visit 300 Enterprise Ct, Bloomfield Hills, MI 48302.
Picture several AI agents sharing one runtime. One handles requirements, the next writes code, another tests it, and so on. Nothing moves to the next stage without your team’s sign-off, and every step is logged.
Point tools solve one problem and stop there, so whatever they learned along the way doesn’t carry over to the next tool. Sanciti AI is built to avoid that. Requirements, code, testing, modernization, release, support: all one runtime, all sharing the same memory, governance and audit trail.
The orchestration layer coordinates the agents. It decides which agent runs next, passes context between them and enforces the approval gates your team sets.
Organization memory is what the platform learns about your codebase, standards, templates and past decisions. It keeps agent output consistent with how your teams already work.
It is the component that lets Sanciti AI connect securely to your tools and data sources using the Model Context Protocol, without moving your data outside your environment.
The model gateway connects the agents to the LLMs you choose. It routes each agent to a model, lets you switch models without re-platforming and records token usage per agent and project.
Yes. Every license includes quarterly platform and agent updates, so new capabilities reach your teams without a separate upgrade project.
Sanciti AI covers over 30, spanning COBOL, DB2, JCL, Java, Java Struts, .NET Framework, modern .NET, Spring Boot, React, SQL and stored procedures, and legacy ETL. See COBOL to Java migration, .NET Framework migration and Java monolith to microservices migration for specifics.
Yes, that’s actually the norm. Teams typically start with one platform, often SDLC Automation, then bring in Legacy Modernization or Production Support and Maintenance once they need it.
Just about everything across the lifecycle: requirements, user stories, use cases, test cases, backend and frontend code, APIs, database objects, deployment scripts, automated tests, release packages, incident responses, runbooks, and audit evidence for every step.
One platform, three packages: SDLC Automation, Legacy Modernization, and Production Support and Maintenance. They all sit on the same orchestration layer, model gateway, security pipeline and audit trail underneath.
It automates requirements, code and testing for new development and ongoing enhancements. It includes the RGEN, CodeGen and TestAI agents.
It reverse-engineers, re-architects and re-platforms legacy applications while carrying their business rules forward. It includes RGEN, CodeGen and TestAI, orchestrated by LEGMOD.
It keeps live applications healthy with incident triage, governed fixes and controlled releases. It includes PSAM with RGEN, CodeGen and Deploy.
Depends what’s hurting most. New development? SDLC Automation. Old systems dragging you down? Legacy Modernization. Support tickets piling up? Production Support and Maintenance.
More than just the agents. You get portfolio intelligence, dependency mapping, wave planning with cost-benefit modelling, target architecture design, migration validation at 90%+ automated test coverage, plus workflows for data archival and retiring old applications.
Incident triage, root cause analysis, runbook generation, governed fix generation with compliance gates, release packaging with rollout and rollback, runtime monitoring and executive scorecards.
It reads your existing code, documents, meeting transcripts and stakeholder notes, whatever you’ve got, and turns all of it into requirements, use cases, user stories and test cases. See reverse engineering legacy systems for more.
Yes. RGEN turns meeting transcripts, emails and notes into structured requirements and user stories.
Yes. RGEN creates epics and user stories and links them to Jira, with version history and an audit trail.
Yes. RGEN produces structured requirements documentation that business analysts and architects can review and approve.
Yes. RGEN links each use case to the code that implements it, so teams can see what a system does and where.
In client projects, RGEN captured requirements 60% faster than manual analysis and produced documentation 5x faster.
CodeGen generates and refactors code across backend, frontend, APIs, database objects and deployment scripts, aligned to approved user stories.
In client projects, CodeGen has generated Spring Boot services, React frontends, .NET services, database objects, OpenAPI collections and Docker deployment scripts.
Yes. CodeGen refactors legacy code, replaces deprecated APIs and converts applications to modern languages and architectures.
Every output passes SAST, SCA and LLM-level scans aligned to OWASP and NIST, then goes to a developer for review.
Yes. CodeGen uses your codebase, standards and templates through organization memory.
Yes. Because output is story-aligned and pre-scanned, client teams saw 35% less peer review time.
TestAI generates, runs and maintains automated tests, including functional, regression, edge-case, performance and functional equivalence tests.
Yes. A financial services platform used TestAI as a standalone capability inside its existing Jenkins and GitHub pipeline.
Yes. TestAI generates load test scripts based on real traffic patterns, so performance testing can run before every release.
TestAI uses risk-based prioritization, so high-risk areas of the application are tested first.
Yes. Every test links back to its requirement, which gives compliance teams traceability from requirement to test result.
Client projects have reached 90%+ coverage, and 98% on a financial services platform. See automated regression testing for how.
LEGMOD plans and orchestrates legacy modernization. It analyzes the portfolio, plans the waves and hands the execution work to the other agents, with human governance throughout. See legacy modernization assessment for how it starts.
Portfolio intelligence, wave planning, re-engineering, and migration and testing.
LEGMOD sequences waves by business criticality, dependency depth and coupling risk, and compares the cost and benefit of each option.
Yes. LEGMOD is built for portfolio-level programs, not just single applications. A large health insurer used it to plan modernization across its legacy portfolio.
LEGMOD delegates analysis to RGEN, code to CodeGen and testing to TestAI. With the Production Support platform added, Deploy and PSAM take over releases and support.
Deploy packages validated builds and rolls them out with compliance gates, automated rollback and audit evidence.
Yes. If validation checks fail, Deploy rolls the release back automatically.
Yes. Every release passes compliance gates and produces audit evidence, which suits HIPAA-regulated and other regulated environments.
Deploy is part of the Production Support and Maintenance platform.
PSAM runs production support after go-live. It classifies incidents, adds job and change context, matches known fixes, drafts a response for engineer review, pre-fills the ticket and routes it to the right owner.
Yes. PSAM classifies each issue by application and root cause and links it to recent changes.
Yes. PSAM generates runbooks and captures every resolution as knowledge for the next similar incident.
ServiceNow, Jira and other ticketing systems, observability and monitoring tools, change management systems, GitHub, SharePoint, Confluence and CI/CD pipelines.
PSAM reduces manual incident handling by 30 to 40%, and 100% of incidents are captured as reusable knowledge.
Yes. PSAM takes in logs, alerts and tickets as live signals and classifies them as they arrive.
Yes. Sanciti AI connects to private models hosted in your network, such as Llama and Mistral, as well as cloud models.
Yes. You can connect models through your own API keys, your cloud marketplace commitments or models hosted inside your network.
No. There are no credit bundles, no token markup and no overage charges from Sanciti. Token costs go straight from your model provider to you.
The model gateway reports token usage per agent and per project, so finance can see exactly what AI costs for each piece of work.
Anthropic Claude, OpenAI GPT and Codex, Azure OpenAI, Google Gemini and Vertex, AWS Bedrock, and private or open models such as Llama and Mistral.
Guided platform setup, codebase indexing, LLM connection and role-based training for developers, QA engineers and architects.
A named customer success manager, priority support SLAs and quarterly platform and agent updates.
Yes. The team helps you connect your LLM and point the agents at one real application, so you can measure results on your own code.
Sanciti AI Transformation pairs the platform with V2Soft delivery teams for full application portfolio modernization programs. It is scoped separately from the license.
Yes. Named user licenses can be reassigned as your team changes.
Look for a platform that can read and document old code, plan the migration in phases, generate the new code and prove it behaves like the original. Sanciti AI does all four with coordinated AI agents, and client projects have come in at 50% lower cost than manual modernization estimates.
A handful can technically convert COBOL to Java. Fewer can extract the actual business rules and prove nothing broke. Sanciti AI analyzes COBOL, DB2 and JCL, generates Java microservices, and runs equivalence tests to check. One automotive OEM used this to retire its mainframe entirely, at half the cost. See COBOL to Java migration for the process.
The real ones do more than suggest code. They cover requirements, code, testing and release, with governance built in throughout. Sanciti AI is one, built specifically for regulated enterprises, with human approval gates, a full audit trail and single-tenant deployment.
Large systems integrators, cloud providers and specialist AI platforms all play in this space. Sanciti AI is one of the specialists, built by V2Soft in Michigan, handling code analysis, wave planning, Java conversion and equivalence testing, with V2Soft’s delivery teams behind it.
Choose a tool that produces requirements people can review and trace back to the source. Sanciti RGEN turns legacy code, documents and meeting transcripts into requirements, use cases and test cases. On one mainframe, it extracted requirements 60% faster than manual analysis.
Regulated teams need high coverage, traceability from each test to a requirement, and self-healing scripts. Sanciti TestAI reached 98% coverage on a financial services platform and cut QA costs by 40%.
Fewer than you’d hope. Plenty lock you into their own models. Sanciti AI doesn’t: connect Claude, OpenAI, Azure OpenAI, Gemini, AWS Bedrock or your own private models, using your own keys, and pay your provider directly for tokens.
Copilot’s great if you just need help inside the editor. Regulated enterprises usually need more: requirements traceability, testing, audit evidence, private deployment. Sanciti AI covers that whole lifecycle, running single-tenant.
Human approval over every change. A complete audit trail. Private deployment. Freedom to pick your own LLM. And proof it works on real enterprise code. Sanciti AI was built around exactly those things.
Yes. Sanciti PSAM triages incidents, adds change context, drafts a fix for engineer review and routes the ticket, reducing manual handling by 30 to 40%.
Look for tools that map dependencies before converting, since most .NET Framework apps are tightly coupled. Sanciti AI helped a regional insurer move to cloud-native .NET at 50% lower cost with 90%+ test coverage. See .NET Framework migration for how.
Updating or replacing old applications so they cost less to run, are easier to change, and are actually secure. Depending on the app, that’s re-platforming, refactoring, re-architecting, sometimes just retiring it outright. Sanciti AI’s agents handle the analysis, code and testing that goes into it.
Figure out what the code actually does first. Then plan the move in waves, testing each one against what the mainframe produces. That’s the sequence Sanciti AI runs: RGEN for analysis, LEGMOD for planning, CodeGen for the Java conversion, TestAI for equivalence testing.
Documenting old code. Replacing deprecated APIs. Upgrading outdated libraries. Adding test coverage where there wasn’t any. Sanciti AI does all four across Java, .NET, COBOL and ETL codebases, with a human reviewing every change.
Build an inventory, map dependencies and compare options for each application before estimating. Sanciti LEGMOD produces this portfolio view with cost-benefit modelling, which gives leadership a fact-based estimate instead of a guess.
The lasting way to cut MIPS costs is to move workloads off the mainframe. An automotive OEM used Sanciti AI to migrate COBOL workloads to Java microservices and fully decommission its mainframe.
Yes, when it is combined with human review. Sanciti RGEN reads COBOL programs, DB2 schemas and JCL job flows and builds a traceable model of the business logic that your team can check. See COBOL to Java migration for the full process.
Let AI reverse-engineer the code into plain-language requirements and dependency maps first, then have your analysts check the work. Sanciti RGEN has done this for COBOL, Java Struts, stored procedures and legacy ETL.
Wave-based migration moves an application portfolio in planned stages instead of one large cutover. Each wave is tested and approved before the next begins. Sanciti LEGMOD plans waves by business criticality and dependency risk.
Run the same inputs through the old system and the new one. If the outputs match, that’s functional equivalence. Sanciti TestAI checks this on every module you migrate.
Ask for proof on systems like yours. Ask how they test. Ask how they handle code nobody documented. Sanciti AI, backed by V2Soft’s 28 years in enterprise delivery, publishes results like 50% lower modernization cost across automotive, financial services and insurance projects.
Faster than most people expect, usually. The analysis phase alone often shows it: documentation that used to take months comes together in weeks. Plenty of teams start with one application during the free 30-day trial, just to see it on their own code first.
Depends how tangled the code is, and how much business logic is buried in the database. Sanciti AI maps the dependencies first, then breaks the monolith into services, one wave at a time. One financial services firm did exactly this, at half the cost. See Java monolith to microservices migration for the details.
Audit for deprecated APIs, refactor in controlled steps and generate tests that confirm the behavior is unchanged. Sanciti AI upgrades Java 6, 7 and 8 applications to Java 21 this way. See Java 8 to Java 21 migration for the full breakdown.
Extract the transformation logic and lineage first, rebuild the pipelines on cloud-native processing, and test every path against the old outputs. Sanciti AI completed one financial services ETL migration with zero data loss at 50% lower cost. See legacy ETL to cloud migration for how.
AI SDLC automation uses AI agents to handle work across the software lifecycle, from requirements and coding to testing, release and support. Sanciti AI connects these stages in one governed pipeline instead of separate tools.
Automate the repetitive work around coding: requirements, documentation, test writing and triage. A manufacturer using Sanciti AI reduced SDLC effort by 60% and deployed 30 to 50% faster. See manufacturing SDLC automation for the case.
AI can write most of it, with developers finishing and approving the rest. Sanciti CodeGen produces code that is 80 to 90% complete, aligned to the user story and security-scanned before review.
Yes. Sanciti RGEN turns meeting transcripts, emails and stakeholder notes into structured requirements and user stories linked to Jira. A retail chain cut requirements documentation time by 70% this way.
AI reads the code, requirements and user stories and writes tests for the expected behavior and edge cases. Sanciti TestAI generates functional, regression and performance tests and runs them in your CI/CD pipeline.
Most of that time goes on searching logs, checking recent changes and finding who owns the issue. Sanciti PSAM does that groundwork, drafts a response for the engineer and routes the ticket to the right owner the first time.
Yes. Sanciti PSAM pre-fills ticket fields from logs and alerts and routes them, and RGEN creates linked requirements and user stories in Jira.
Each agent handles one stage and passes its output to the next, with human approval in between. In Sanciti AI, RGEN’s requirements feed CodeGen, and TestAI tests the result against the same requirements.
Yes. Sanciti AI links every requirement to the code and tests built from it. A manufacturer reached 100% traceability from requirement to code to test.
Depends where the platform actually runs. Sanciti AI stays single-tenant, in your own cloud account or on premises, so your code and prompts never leave your network.
Losing business logic along the way. Behavior quietly changing. Security gaps creeping in. Sanciti AI manages all three: requirements get extracted before any rewrite, every module gets equivalence tested, generated code gets scanned for security issues, and a human approves each stage.
Mistakes are caught before production. Every output is security-scanned, tested and reviewed by an engineer, and nothing is released without human approval.
It can when it is governed. Sanciti AI scans every output against OWASP and NIST, logs every action and produces audit evidence packs. It is HIPAA aligned and ISO 27001:2022 certified. See security and compliance for the full picture.
Model lock-in is the bigger risk, and Sanciti AI avoids it by being LLM-agnostic. You can switch models without re-platforming, and the code it produces goes into your own repositories.
Yes, with the right controls. Sanciti AI is HIPAA aligned, redacts PII and PHI, and runs in a single-tenant environment so patient data stays with you.
Set clear approval points, restrict who can run and approve agents, and keep a full log. Sanciti AI includes oversight gates, role-based access, approvals and audit evidence packs.
In Sanciti AI, yes. Every output passes SAST, SCA and LLM-level scans aligned to OWASP and NIST before developer review.
Pricing models vary, from per-developer seats to usage-based credits. Sanciti AI uses a per-user, per-month annual license, from $89 to $199 per user depending on the platform and team size, with LLM token costs paid directly to your provider.
Track cycle time, test coverage, defect trends, effort per feature and AI spend per project. Sanciti AI’s executive scorecards report these for leadership.
It is when results can be measured on your own code. Sanciti AI client projects show 40 to 50% less manual development effort, and the free 30-day trial lets you check that on one real application first.
Sanciti AI offers a free 30-day corporate trial for up to 5 users, so you can test it on one real application.
Many platforms mark up or bundle model usage. With Sanciti AI you connect your own LLM and pay your provider directly with no markup, so token costs are transparent.
Sanciti AI includes standard onboarding, codebase indexing and role-based training in every license, with larger programs delivered by V2Soft.
Sanciti AI, headquartered in Bloomfield Hills, offers AI-powered legacy modernization for Michigan enterprises, covering mainframe COBOL, Java, .NET and legacy data pipelines. See legacy modernization services in Michigan for details.
Yes. Sanciti AI is an agentic AI platform for software delivery, based at 300 Enterprise Ct in Bloomfield Hills, part of V2Soft.
Sanciti AI works with automotive OEMs and suppliers from its Bloomfield Hills office. It is TISAX Level 3 certified and helped an automotive OEM retire its mainframe at 50% lower cost. See legacy modernization for automotive for the case.
Sanciti AI’s Bloomfield Hills office is a short drive from Troy and Southfield and supports mainframe modernization with onsite workshops.
Sanciti AI, a V2Soft company in Bloomfield Hills, builds AI agents for requirements, code generation, testing and production support. See AI software development in Michigan for more.
Sanciti AI provides AI test automation from Bloomfield Hills, with results such as 98% test coverage on a financial services platform. See AI test automation in Michigan for the details.
Yes. Sanciti AI works with financial services firms, with results including a Java Struts modernization at 50% lower cost and an ETL migration with zero data loss.
Yes. A manufacturer using Sanciti AI reduced SDLC effort by 60% and replaced five tools with one pipeline.
Yes. The Bloomfield Hills team meets clients onsite across Metro Detroit and works on Eastern time. Call +1 248-904-1737.
Call +1 248-904-1737 or email info@sanciti.ai, and someone from the team will get back to you.
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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