Hakuna Matata Solutions

Identify AI deployment blockers and get a prioritized roadmap for production readiness.

Improve workflows, enterprise knowledge access, and forecasting with integrated, governed AI designed for production.

Modernize legacy applications while preserving business logic and keeping live operations stable through phased delivery.

Deliver production-ready software faster with AI-accelerated engineering, sound architecture, and applications designed for long-term operation.

Turn Figma designs into production-ready frontend code faster and fit generated code into existing development workflows.

Modernize legacy backends with REST APIs and modular services while preserving business logic and avoiding full rewrites.

Move data between databases with validation, minimal downtime, controlled processing, and audit-ready visibility.

Give teams access to verified database insights in plain English while reducing routine data requests to technical teams.

Automate document-driven workflows to reduce manual work and help teams increase output without adding headcount.

Automate business processes and connect enterprise systems with custom applications designed to scale and remain maintainable.

Build cloud-native applications that scale with demand and give teams the tools to deploy, operate, and observe their platforms.

Build secure, integrated iOS and Android apps for enterprise workflows with offline capability and maintainable delivery.

Build and scale products with aligned architecture, consistent engineering teams, analytics from the first release, and accelerated delivery.

Validate user experiences before development and give product teams consistent, accessible interfaces they can extend.

Build scalable, production-ready web applications with enterprise integrations and architecture designed for long-term operation.

Capabilities that help enterprise IT and engineering teams refactor legacy applications, migrate mainframes, automate development and testing, and maintain modernized systems.

Products: ADaM (Accelerated Development and Modernization), AI-driven Application Modernization Services, DB Migration, Cloud-native Development

End‑to‑end design, development, integration, and modernization of bespoke enterprise and consumer web and mobile applications.

Products: AI-led Software Engineering, Business Application Development, Cloud-native Development, Mobile App Development, Niral.ai, Product Engineering, UI/UX Design & Prototyping, Web Application Development

Services and platforms that help enterprises assess AI readiness, develop custom models and agents, integrate enterprise systems, and deploy governed workflow automation.

Products: AI Readiness Assessment, Enterprise AI Solutions

Automation that combines AI agents, NLP, and intelligent document processing to handle unstructured data, make decisions, and automate complex workflows.

Products: Nunar, Enterprise AI Solutions, Business Application Development

Natural-language interfaces that let business users query enterprise databases and retrieve grounded answers without writing SQL, subject to existing data access controls.

Products: Chat to SQL

AI Readiness Assessment

A two-week diagnostic that reviews legacy systems, data architecture, and AI deployment readiness through workshops and asynchronous review. It identifies technical and data-related blockers, maps the current state against production-ready AI requirements, and provides a prioritized, sprint-ready modernization roadmap shaped around organizational constraints. The assessment concludes without a vendor pitch.

• Prioritize Your Next Actions
  Get practical next steps tailored to constraints rather than a generic template.
• Reveal Legacy Deployment Blockers
  Pinpoint systems and technical debt that prevent AI deployment so teams can target relevant constraints.
• Assess Data Readiness
  Review data pipelines and quality gaps to understand whether the data architecture can support AI workloads.
• Map Production Readiness Gaps
  Clarify the gaps that must be addressed before AI deployment.
• Get Findings In Two Weeks
  Receive the assessment report in a defined timeframe for planning next steps.
• Review Readiness Through Workshops
  Use collaborative workshops and asynchronous review to examine technology and readiness.
• Get Findings Without A Sales Pitch
  Receive findings and a roadmap without an end-of-engagement vendor pitch.

Enterprise AI Solutions

Custom enterprise AI solutions address specific business problems, connect to operational data, and fit into existing workflows. Capabilities include retrieval-augmented knowledge systems, predictive and forecasting models, AI agents, workflow automation, and governance for secure, auditable deployment. Work can cover use-case definition, data readiness, integration mapping, model and architecture choices, implementation, monitoring, and governance. The architecture is model-agnostic and designed to support existing systems and ongoing maintenance. Related consulting and development capabilities include feasibility analysis, data engineering, model development, evaluation, failure handling, and pilot-to-production enablement.

Category: AI Development Services

• Automate Repetitive Operational Work
  Handle high-volume workflow tasks through agents and automation embedded in existing processes, with defined boundaries and escalation paths.
• Govern AI From Day One
  Oversee model performance, accuracy, data access, and inference costs throughout deployment and operation.
• Integrate AI Into Existing Workflows
  Use AI capabilities within existing processes and infrastructure rather than as standalone tools.
• Retrieve Relevant Enterprise Knowledge
  Connect enterprise information to user queries to make institutional knowledge easier to find and use.
• Validate AI Opportunities Before Building
  Align AI work with business problems, available data, integration requirements, and measurable outcomes.
• Move AI From Strategy To Production
  Prepare AI systems for operational use with deployment, integration, monitoring, and governance.
• Improve Operational Forecasting
  Provide forecasts and anomaly insights within workflows to support decisions involving demand, capacity, and resources.
• Avoid Dependence On One Model Provider
  Change or upgrade models while retaining the AI system and its integrations.

AI-driven Application Modernization Services

Transforms legacy applications into scalable, API-enabled architectures while preserving core business logic and maintaining operational stability. An AI-powered discovery engine maps integrations, hidden business rules, and system risks before code changes. Modernization can address user interfaces, backend services, and data layers, including monolith-to-microservices transformation and Oracle Forms modernization. Work is phased and rollback-ready, with Niral.ai and ADaM supporting interface generation, service extraction, and API generation.

• Map Hidden Logic And Dependencies
  Surface integration points, undocumented business rules, and system risks before modernization starts.
• Modernize In Reversible Phases
  Validate each stage and retain a rollback path while new components are proven.
• Modernize Application Layers
  Address interfaces, backend architecture, APIs, databases, and cloud deployment through appropriate modernization tracks.
• Preserve Validated Business Rules
  Carry established business processes into modern platforms rather than discarding or reinterpreting legacy logic.
• Accelerate UI And Backend Delivery
  Use engineering accelerators for repeatable UI and backend implementation work.
• Move Legacy Forms To Modern Web Platforms
  Replace legacy Forms interfaces and address coupled database logic while validating the modernized application against the original.
• Choose A Fit-For-System Path
  Match modernization work to system condition and needs, avoiding unnecessary architectural change.
• Connect Systems To AI Platforms
  Make legacy business functionality accessible to modern platforms and AI, analytics, and automation tools through APIs and modular architecture.

AI-led Software Engineering

AI-led software engineering for mobile, web, enterprise, and cloud-native SaaS applications. Engagements assess operational requirements, integration dependencies, and whether to build, buy, or extend existing systems. AI accelerators support design-to-code, code scaffolding, and test coverage, while engineers focus on architecture, integration, and maintainability. Delivery includes secure deployment, CI/CD controls, upgrade paths, and observability, with co-engineering, end-to-end ownership, and project-based engagement options.

Category: Custom Software Development Services

• Accelerate Development With AI-Powered Tools
  Niral.ai generates frontend code and ADaM supports backend scaffolding, allowing engineers to focus on architecture and integration.
• Choose The Right Build Approach
  Evaluate development, SaaS configuration, and extensions before committing to an approach.
• Build Applications Across The Full Stack
  Develop applications across mobile, web, enterprise, and cloud-native SaaS contexts.
• Build For Reliable Long-Term Operation
  Plan architecture and integration while accounting for deployment controls, upgrades, and ongoing observability.
• Choose A Delivery Model That Fits
  Select an engagement model aligned with the work and the client's engineering process.

Niral.ai

A design-to-code platform that converts Figma designs into responsive frontend code for React, Angular, Vue, and other frameworks. Users can set framework, layout, and styling preferences, map Figma components to existing codebase equivalents, preview generated code, and commit it to a Git branch. Generated code is readable and reusable without a proprietary wrapper. The platform also flags design inconsistencies, missing constraints, and unnamed layers during upload.

• Convert Designs Into Production Code
  Generate frontend code directly from Figma designs to move from design to implementation more quickly.
• Build For Your Preferred Framework
  Choose a supported framework suited to the project's technology and workflow.
• Reuse Existing Design System Components
  Reuse component mappings to support consistency with existing design systems.
• Edit And Extend Generated Code
  Use familiar development practices to work with generated output.
• Catch Design Issues Before Generation
  Identify common Figma file problems before generating code.
• Review And Export Generated Code
  Review generated code and download it or commit it to a Git branch.

ADaM (Accelerated Development and Modernization)

A backend modernization accelerator that transforms legacy backend logic, including PL/SQL and stored procedures, into REST APIs and modular microservices. It combines API generation, reusable microservice templates, CRUD generation, and CI/CD deployment templates to support phased modernization without a full rewrite. ADaM is designed for enterprise security, compliance, and DevOps integration.

• Expose Legacy Logic Through REST APIs
  Make existing PL/SQL business logic accessible through REST APIs for integration with modern platforms.
• Decompose Backends Into Modular Services
  Move toward independently deployable services without requiring a full-system rewrite.
• Build Services With Reusable Components
  Use prebuilt microservices, templates, and CRUD generation to accelerate modular backend development.
• Support Enterprise Security And Compliance
  Establish access controls and align backend modernization with enterprise security and DevOps requirements.
• Deploy Services With Production-Ready CI/CD
  Use deployment templates to support production delivery of modernized services.
• Deploy Across Major Cloud Platforms
  Use an architecture designed for multiple major cloud platforms.

DB Migration

Database migration tooling for moving data between databases through a structured, validated process. It supports schema changes, custom field mappings, data cleaning and enrichment, and validation before, during, and after transfer. Batch processing or CDC can extract data without disrupting live systems, while phased cutover and synchronization help maintain availability. The platform includes retries, restart-from-failure capabilities, centralized monitoring, transaction-level audit logs, flexible target loading, and cloud and hybrid deployment models.

• Move Data Between Database Systems
  Migrate data without restricting the source and target to a single database pairing.
• Protect Data Accuracy
  Validation and record-level traceability help verify data consistency and completeness.
• Keep Systems Available
  Migration and synchronization options help minimize downtime and user disruption.
• Adapt Data To Target Schemas
  Map fields, handle schema changes, and address data inconsistencies during migration.
• Resume Processing After Failures
  Resume migration after a failure without restarting from the beginning.
• Maintain Audit-Ready Records
  Track migration stages and transactions to support traceability and audit requirements.
• Protect Data Across Deployment Models
  Protect sensitive information during transfer and select a target loading method suited to the migration.

Chat to SQL

An AI-powered interface that converts natural-language questions into database queries and returns verified answers from existing databases. Users can retrieve insights without writing SQL. The solution uses read-only access, RAG-grounded responses, and role-based permissions, while keeping raw database data in the customer's environment. It supports multiple database platforms and requires no structural database changes.

• Query Data Without Writing SQL
  Help business users retrieve structured insights using natural-language questions.
• Get Answers Grounded In Real Data
  Provide database-backed information when users explore data.
• Query Data With Controlled Access
  Retrieve information without changing records and limit database access according to user roles.
• Connect To Existing Databases
  Use the solution with supported databases in the current data architecture.
• Keep Raw Data In Your Environment
  Keep raw database data within the customer's environment.
• Export And Share Data Results
  Make retrieved insights available for further analysis and decision-making.

Nunar

An AI-powered enterprise automation platform that reads incoming data from WhatsApp, email, PDFs, scanned documents, and spreadsheets. AI agents extract, validate, and structure information, then update ERP, CRM, or other enterprise systems. Nunar connects with tools such as spreadsheets and Slack and can be configured around organizational workflows. Security controls include encryption, role-based access, and secure API communication, with on-premise and private-cloud deployment options.

• Automate Repetitive Enterprise Work
  Reduce manual effort by automating workflow steps such as message processing and business record updates.
• Process Data From Existing Sources
  Automate workflows using messages, documents, and spreadsheets across multiple formats.
• Prepare Data For Enterprise Systems
  Prepare incoming information for use in ERP, CRM, and other enterprise systems.
• Connect Workflows To Business Systems
  Move processed information into connected business systems and existing tools.
• Protect Data With Enterprise Controls
  Protect information with access controls, encryption, secure communications, and private deployment options.
• Fit Automation To Your Workflows
  Match AI workflows to organizational processes and operational requirements.

Business Application Development

Designs and develops custom business applications for internal operations, customer portals, analytics platforms, workflow automation, financial software, SaaS platforms, MVPs, and desktop applications. Applications are mapped to business processes and designed for integration, scalability, and maintainability. The service covers architecture, application and integration development, workflow automation, testing, deployment, CI/CD, maintenance, and performance tuning. Related custom enterprise application work includes build-versus-buy assessment, data migration planning, production readiness, and handover of source code, documentation, architecture assets, and CI/CD pipelines.

Category: Custom Software Development Services

• Build Applications Around Your Operations
  Get applications tailored to business workflows rather than a generic feature set.
• Connect Applications Across Enterprise Systems
  Enable data to flow between applications and enterprise platforms, reducing manual transfers and duplicate entry.
• Align Applications With Real Workflows
  Base application design on actual business processes, decision points, and exceptions.
• Build Maintainable Application Foundations
  Establish an architecture intended to remain flexible and maintainable as requirements and business scale change.
• Automate Complex Business Workflows
  Reduce manual effort and operational inefficiencies through workflow automation.
• Protect Sensitive Business Data
  Govern access to sensitive information and support enterprise security requirements.
• Evolve Applications With Changing Needs
  Support applications after delivery through maintenance, performance tuning, and continued improvement.
• Own And Extend Your Application
  Give client teams the assets needed to maintain and extend applications after delivery.

Cloud-native Development

Cloud-native development across AWS, Azure, and GCP. The service assesses workload, team, and operational needs before recommending an architecture, then builds containerized applications, infrastructure-as-code, and DevOps pipelines. It includes deployment controls, observability, and cost governance, with ADaM and Niral.ai accelerators supporting backend setup and operational interfaces.

• Choose An Architecture That Fits
  Match architecture to workload and team needs while avoiding unnecessary operational overhead.
• Deploy Changes With Confidence
  Automated checks and deployment controls help reduce risks associated with manual releases.
• Scale Workloads With Demand
  Support changing workloads through containerization and auto-scaling.
• Observe Systems And Manage Costs
  Monitor systems from go-live and establish practices to track and manage cloud costs.
• Automate Infrastructure Provisioning
  Reduce repetitive configuration work through infrastructure-as-code and reusable provisioning scripts.

Mobile App Development

Develops native and cross-platform mobile applications for enterprise workflows on iOS and Android. Apps address offline capability, role-based access, security policies, device management, and integration with ERP, CRM, and identity systems. The service covers native development, React Native, Flutter, and hybrid apps, with AI-assisted UI development and backend scaffolding. Delivery includes CI/CD for app stores and enterprise MDM distribution, documented components, versioned APIs, and upgrade paths.

• Choose The Right Platform Approach
  Select native or cross-platform development according to use case, performance, and maintenance needs.
• Protect Enterprise Data
  Address security and access requirements from the architecture stage.
• Connect Mobile Apps To Enterprise Systems
  Connect mobile applications to existing enterprise systems through planned integration architecture.
• Support Work Across Devices
  Build offline and device-management requirements into enterprise mobile workflows.
• Prepare Apps For Distribution And Maintenance
  Support app distribution and give teams a foundation for ongoing maintenance and extension.

Product Engineering

End-to-end product engineering covering discovery, strategy, architecture, development, QA, release, and iteration. Engagements combine dedicated engineering teams, business intelligence designed into the product from the architecture stage, and AI-accelerated delivery. Work includes enterprise web applications, mobile products, SaaS platforms, BI-embedded products, and AI-native applications, with teams accountable to product outcomes across sprints.

• Align Teams Before Development Begins
  Establish shared context on objectives, architecture, and priorities before implementation.
• Retain Product Knowledge Across Sprints
  Reduce re-onboarding and handoff risk while supporting feature delivery.
• Deliver Analytics From The First Release
  Provide product users and operators with visibility into product performance and operations.
• Accelerate Production-Ready Screen Delivery
  Reduce manual UI implementation work and support consistent screen delivery.
• Manage Products From Discovery To Iteration
  Support products beyond initial delivery as requirements and scale evolve.

UI/UX Design & Prototyping

Enterprise UI/UX design services take products from discovery to production-ready screens. Work includes user-flow mapping, usability research, wireframes, interactive prototypes, design-system architecture, and responsive, accessible interfaces. Designs account for user roles, component states, edge cases, and backend integrations. Figma designs built to Niral.ai component standards can generate frontend code. Design decisions are documented and version-controlled.

• Generate Front-End Code From Designs
  Connect design intent to implementation and reduce manual interpretation and rework.
• Build Consistent, Reusable Interfaces
  Support interface consistency and reduce the need to reinterpret elements as products evolve.
• Validate User Flows Before Development
  Identify usability issues before development begins.
• Test Interactions Before Development
  Review user flows and interactions before committing to full development.
• Support Accessible, Responsive Experiences
  Design interfaces for accessibility and use across devices.

Web Application Development

Develops production-ready web applications, including portals, dashboards, customer-facing products, progressive web apps, and content-managed platforms. The service combines AI-accelerated frontend development with architecture and integrations planned before implementation. Applications use frameworks such as React, Angular, and Vue.js, with backend technologies including Node.js, Python, and Java. Delivery addresses role-based access, multi-tenant architecture, security, performance, CI/CD, observability, and maintainability.

• Accelerate Frontend Implementation
  Reduce repetitive screen work so developers can focus on application logic and architecture.
• Resolve Architecture Before Coding
  Establish a stable foundation and address enterprise requirements early.
• Connect Enterprise Systems From The Start
  Define integration contracts early to reduce integration rework.
• Prepare Applications For Live Operations
  Prepare applications for ongoing use rather than demonstrations only.
• Choose Frameworks For Your Requirements
  Select technologies according to integration, team, and maintenance needs.
• Deliver Flexible Browser-Based Experiences
  Provide app-like browser experiences and allow teams to manage content without engineering support for every update.