Engineered for what’s next. We dismantle monolithic constraints, enabling your applications to embrace AI, open-source economics, and high-performance hardware for total digital liquidity

Architectural Evolution

agntStorm10: Architectural Reverse Engineering

Legacy applications are often "tribal knowledge" traps—monolithic systems where the original developers are gone, and the documentation is non-existent. When leadership wants to modernize or integrate GenAI, they are met with a "Black Box." Understanding what the code actually does from a business perspective usually requires months of manual discovery, interviews, and guesswork. Without a clear map of the application’s events and commands, any attempt at modernization is a shot in the dark that risks breaking mission-critical hidden logic.
agntStorm10 acts as a linguistic and structural translator. By performing a deep static analysis of the source code, it automatically generates a high-fidelity Event Storming board. It maps the 7-color domain-driven design (DDD) schema—identifying Actions, Events, Actors, and External Systems—without requiring a single interview. This provides an immediate, visual baseline of the application’s true functionality. The result is a "Business Logic Blueprint" that allows you to identify GenAI use cases, pinpoint modernization bottlenecks, and bridge the gap between legacy code and future-state architecture in a fraction of the time

Most GenAI initiatives fail not because of the AI, but because of "Context Blindness." Organizations attempt to bolt LLMs onto legacy systems without understanding if their data is "AI-accessible" or which workflows actually benefit from intelligence. Without a forensic evaluation of the application's underlying logic—often hidden in spaghetti code or undocumented schemas—businesses end up with generic chatbots that lack business-specific context and fail to solve actual operational bottlenecks.
agntGen10 turns architectural insights into an AI roadmap. By ingesting the event-driven maps generated by agntStorm10, it identifies "Intelligence Nodes"—specific points in your workflow where multi-modal LLMs or RAG can replace manual data entry, complex decision-making, or customer support hurdles. It evaluates your DB schemas for semantic readiness and projects the ROI of specific AI integrations. The result is a high-velocity transition from legacy "static" software to an "intelligent" ecosystem, ensuring your AI spend is targeted at the highest-impact use cases

agntGen10: GenAI Readiness & Use-Case Engine

The dream of "infinite cloud scale" often dies at the application layer. Many legacy applications are "Stateful"—they store session data, local files, or temporary configurations directly on the server they inhabit. This creates a hard "tether" that prevents the app from being containerized or running in elastic environments like Kubernetes or Auto-scalers. If that specific server fails or tries to scale, the user session breaks. Identifying these hidden "state anchors" manually within millions of lines of code is like looking for a needle in a haystack, often leading to migration failures or "Cloud-Wash" where the app runs in the cloud but gains none of its benefits.
agntElas10 performs a deep-tissue scan of your application's source code to identify every "stateful" dependency. It maps local file I/O, hardcoded IP addresses, and in-memory session variables that prevent horizontal scaling. Beyond just finding the problems, it provides a surgical refactoring guide—recommending the exact code changes needed to move state to external caches (like Redis) or object storage (like S3). The result is a truly Elastic Application: a stateless, cloud-native asset that can scale on demand, survive server failures, and deliver a seamless user experience across any boundary..

agntElas10: App Elasticity Assessment

Commercial databases like Oracle and SQL Server are often the single most expensive line items in a technology budget. Beyond the "license tax," these systems lock organizations into proprietary ecosystems, making it nearly impossible to leverage cloud-native innovations or open-source economics. Many teams want to migrate to PostgreSQL or MySQL, but they are paralyzed by "Schema Dread"—the fear that stored procedures, triggers, and complex data types will break during translation, leading to data corruption or performance degradation that could take months to fix.
agntOpen10 automates the "translation layer" of DB modernization. It performs a forensic scan of your source schemas, identifying every incompatible function, proprietary data type, and complex stored procedure. Instead of a vague report, it provides a detailed Gap Analysis and generates automated script recommendations to handle the conversion. By quantifying the complexity of the move before it begins, it allows you to budget with precision. The result is a de-risked transition to open-source data layers that slashes costs by up to 80% while increasing your architectural agility..

agntOpen10: Open Source Adoption assessor

Hidden deep within the data center are thousands of "Ghost Processes"—legacy batch jobs, cron tabs, and Windows Task Schedulers that keep the business running but operate in a total vacuum. These processes are often "black boxes" with no central observability, no error-handling, and no ability to scale. They represent a massive risk: if a job fails, the business only finds out when the data is missing. Furthermore, because these jobs are tied to fixed servers, they prevent organizations from using low-cost cloud compute, forcing them to pay "always-on" prices for "sometimes-on" work.
agntFlow10 brings legacy execution logic into the light of the modern cloud. It forensicly analyzes your existing schedulers and batch dependencies, translating them into cloud-native orchestration patterns like Azure Logic Apps, AWS Batch, or Power Automate. By decoupling the logic from the server, it enables the use of SPOT instances—the cheapest compute available on the cloud—slashing batch processing costs by up to 90%. The result is a highly observable, self-healing, and scalable execution layer that turns "invisible" background tasks into high-performance, cost-optimized assets.

agntFlow10: Batch and Scheduler Modernization assessor

Debt Management

Clean the slate. We quantify technical debt and automate framework upgrades to transform aging codebases into lean, efficient, and sustainable digital assets

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Organizations are often held hostage by "Version Lock." Apps running on deprecated frameworks—like .NET 4.5, Java 8, or Python 2—become increasingly difficult to secure and impossible to integrate with modern cloud services. The gap between legacy code and current stable releases grows every year, creating a "Dependency Hell" where one update breaks ten other things. Manual upgrades are notoriously slow and error-prone, leading teams to abandon modernization altogether, which leaves the enterprise exposed to unpatchable security vulnerabilities and skyrocketing technical debt
agntLift10 automates the heavy lifting of framework and library migrations. By performing a semantic scan of your codebase, it identifies deprecated syntax, "breaking changes," and obsolete dependencies. It doesn't just flag problems; it suggests the specific syntax updates and library swaps required to reach the latest stable release. The result is a radically accelerated upgrade cycle that moves applications from "Legacy" to "Current" in a fraction of the time. This also facilitates the usage of latest silicons viz. ARM64 chipset, that has a potential of providing up to 40% better Price performance ratio.

agntLift10: Framework Evolution Engine

In the modern enterprise, "bloated code" is no longer just a performance issue—it’s an environmental and financial liability. Legacy applications often run inefficient loops, redundant data transfers, and "zombie" processes that consume excessive CPU cycles and storage. This "digital carbon" not only inflates cloud bills but also prevents organizations from meeting increasingly strict global ESG (Environmental, Social, and Governance) mandates. Without a way to measure the physical energy impact of software, sustainability remains a vague corporate goal rather than an engineering discipline.
agntGreen10 transforms Sustainability into a precision metric. It evaluates your code efficiency and infrastructure utilization to provide a definitive "Sustainability Score" and carbon footprint projection. By identifying "hot spots" where refactoring can reduce CPU cycles and memory overhead, it provides a roadmap to GreenOps—the intersection of environmental responsibility and cost optimization. The result is a dual victory: a significantly reduced carbon footprint and a leaner, more cost-efficient cloud estate that proves high-performance engineering is the ultimate driver of corporate sustainability

agntGreen10: GreenOps and Carbon Scorer

Velocity Engineering

Move faster with certainty. By automating testing and accurately estimating effort, we eliminate bottlenecks and provide the mathematical precision needed for rapid, reliable delivery

agntMeter10: Modernization Effort Estimator

The number one reason modernization projects stall in the boardroom is "Estimation Anxiety." Traditional project scoping relies on manual "finger-in-the-wind" guesswork, which often leads to 2x or 3x budget overruns and missed deadlines. When technical teams can’t provide a precise answer to "How long will this take?" and "What will it cost?", stakeholders treat modernization as an open-ended risk rather than a strategic investment. This lack of predictability keeps critical systems trapped in legacy states simply because the "unknown" is perceived as too expensive.
agntMeter10 replaces guesswork with mathematical certainty. It is a logic-based engine that ingest application attributes—including code complexity, cyclomatic density, and dependency maps—to calculate the exact man-hours required for transformation. By analyzing the "DNA" of the application, it provides a granular breakdown of effort by module and complexity tier. The result is a high-fidelity business case that allows leadership to approve modernization projects with total confidence, knowing that the timelines are backed by code-level evidence rather than optimistic estimates.

The biggest fear when modernizing a legacy application is the "Regression Ripple Effect"—changing one line of code and inadvertently breaking five mission-critical business functions. Most legacy systems lack a comprehensive unit or integration test suite, meaning developers are effectively "flying blind" during refactoring. Building these tests manually after years of development is an exhausting, multi-month task that most organizations can't afford, leaving them to choose between "risky modernization" or "safe stagnation."
agntTest10 creates a digital safety net where none existed. It works by observing the legacy application in production or a staging environment, capturing real-world execution paths, data flows, and state changes to auto-generate a baseline of unit and integration tests. This "Shadow Testing" approach ensures that you have a 100% accurate snapshot of how the system currently behaves before you change a single line of code. The result is a "Zero-Regression" modernization path, allowing your engineers to refactor with speed and boldness, knowing that the automated suite will instantly flag any deviation from established business logic.

agntTest10: Automated test-Suite Generator