Introduction: At SDLC CORP, we specialize in transforming warehouse operations with Odoo Warehouse Management solutions. With years of experience integrating Odoos advanced ERP features, we optimize stock management, streamline order fulfillment, and boost warehouse efficiency. As trusted Odoo experts, we deliver customized solutions that ensure smooth operations, real-time visibility, and better decision-making for your business. Challenges: Managing warehouse operations can be challenging, especially with fluctuating inventory, order fulfillment pressures, and the need for accurate real-time data. Many businesses face issues like disconnected systems, stock discrepancies, and time-consuming manual processes. Our solutions provide automation, seamless integration, and scalability to address these challenges effectively. Solutions: SDLC CORP's Odoo Warehouse Management solutions automate workflows, improving accuracy and reducing errors. By utilizing features such as barcode scanning, real-time stock tracking, and automated replenishment, we integrate seamlessly into your existing business processes. Our certified Odoo consultants ensure your system meets specific needs, boosting operational efficiency and minimizing manual tasks. Impact: The impact of our Odoo solutions on your bottom line is significant. Clients who adopt our system see improvements in inventory control, fulfillment speed, and reporting accuracy. Our commitment to high-quality Odoo integrations has made us a trusted partner in optimizing warehouse management for businesses of all sizes. Results: With SDLC CORP's Odoo Warehouse Management, businesses experience faster inventory turnover, reduced stockouts, and optimized stock levels. Our solutions lead to cost savings, increased warehouse throughput, and higher profitability, reinforcing our position as a leader in Odoo-based warehouse management solutions.
SDLC CORP
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SDLC CORP Portfolios
The project of Odoo Training Services, created by SDLC CORP, provided customized training to ensure employees could maximize the potential of Odoo ERP. Our training programs were tailored to suit various levels of expertise, from basic users to system administrators. Interactive workshops, online webinars, and on-demand video tutorials, ensuring flexibility and convenience for teams. By focusing on role-specific needs, the SDLC CORP ensured employees were equipped with the knowledge to operate Odoo efficiently, improve productivity, and drive business success, and also offered post-training support to ensure continued learning.
Introduction: SDLC CORPs Odoo Trading solutions are designed to help businesses in the trading industry streamline their operations, from procurement and inventory management to sales and distribution. Our expertise in Odoo ERP allows us to deliver customized solutions that enhance your trading processes, improving efficiency and reducing costs. With our guidance, you can optimize your trading operations and gain a competitive edge in the market. Challenges: The trading industry faces several challenges, including managing large volumes of stock, ensuring accurate inventory records, and responding quickly to market changes. Without a unified system, businesses often experience inefficiencies, delays, and errors that impact their bottom line. SDLC CORPs Odoo Trading solutions provide a reliable, integrated platform to address these issues and streamline operations. Solutions: Our Odoo Trading solutions enable seamless management of procurement, sales, and inventory processes. We customize Odoos trading modules to suit your business needs, providing real-time insights, automated workflows, and improved communication across departments. This integration helps your business react quickly to market demands, manage inventory efficiently, and improve supplier relationships. Impact: With SDLC CORPs Odoo Trading solutions, businesses gain greater visibility into their trading processes, reduce operational inefficiencies, and enhance decision-making. The ability to track and manage inventory in real time, coupled with automated workflows, has a significant impact on improving operational performance and customer satisfaction. Results: Clients who adopt our Odoo Trading solutions report faster order processing, reduced stockouts, and improved supplier relationships. The result is a more efficient trading operation that drives growth and ensures better control over your inventory and distribution networks.
The project of Stratify, Odoo Migration Services, was offered by SDLC CORP to provide businesses with a smooth transition from legacy systems to Odoo’s powerful ERP platform. Our team of experts managed the entire migration process, from data extraction and transformation to seamless loading into Odoo, ensuring minimal disruption to business operations and complete data integrity during the transition. With SDLC CORP, businesses effortlessly migrated critical data such as financial records, inventory data, and customer information, while preserving business continuity, also offered post-migration support and training to help teams adapt to the new system effectively.
Mama Drones is an agriculture-focused drone service company in India providing drone sales, spraying services, training, repair, maintenance, and multilingual customer support to farming operations. Their internal processes across sales, field operations, inventory, and service were largely manual, and training and field demonstrations lacked a scalable digital format. SDLC Corp assigned 15+ team members to build a connected operations system using Digital Twins, AR/VR, hardware-software synchronisation, and Odoo ERP. The team built virtual Digital Twin models of the drone hardware with hardware-software sync to maintain accuracy between the physical devices and their digital counterparts. On top of this, AR/VR modules were developed for three use cases: drone operator training, field demonstration walkthroughs, and maintenance guidance. Farm boundary mapping and spraying path visualisation were also built to support field operations. The Odoo ERP implementation covered lead management, customer records, inventory tracking, scheduling, invoicing, and support workflows, consolidating the business operations side of the company into one system. The tech stack included ARCore, ARKit, ARToolkit, and Unity for the AR/VR layer, with Node.js, Python, React, and JavaScript across the platform backend and frontend. Outcomes: 30 to 40% reduction in manual coordination across sales, service, inventory, and field operations; 40 to 50% improvement in training and demo experience using AR/VR models and visualisation; 25 to 30% faster lead and customer follow-up through Odoo CRM and workflow tracking. Delivered across an 18-month engagement and rated 5.0 across all four categories.
Pulastya AI provides AI services for government and enterprise clients. The engagement involved building a district-level digital health platform to replace fragmented manual healthcare workflows used across government health programs. The platform serves three distinct user types simultaneously: doctors managing patient care, field healthcare workers handling community-level data collection, and district administrators overseeing program performance. SDLC Corp built both web and mobile applications on the same platform. The core system handles patient registration and manages condition-specific clinical workflows, with each workflow configured to the operational requirements of the relevant health program. A healthcare analytics module processes patient and program data and surfaces it through real-time dashboards built for district administrators, supporting disease surveillance and program monitoring across the region. On the integration side, the platform connects with existing healthcare databases, medical devices, and government health systems. Role-based access control is implemented across all three user types with permissions scoped to each role. The platform is deployed on secure cloud infrastructure and includes annual maintenance, ongoing feature enhancements, user training, and technical documentation as part of the engagement. The platform supports programs serving over 500,000 citizens, manages 25,000+ patient records, and is actively used by 100+ healthcare professionals and district administrators. Following the initial deployment, the scope expanded into additional governance solutions including legal case management.
Ease Pet Vet runs specialist veterinary behavior programs across clinics in the US and Canada. Their website needed an AI chatbot capable of handling two distinct visitor types, pet owners and veterinary hospitals, each requiring a different conversation flow and lead qualification logic. Alongside the chatbot, their internal operations had manual bottlenecks in two areas: customer onboarding and medication support for their behavior specialty service. SDLC Corp built and deployed a dual-audience AI chatbot. The chatbot identifies visitor intent at entry and routes each user through a separate flow, one designed for pet owners seeking behavior support, the other for veterinary hospitals looking to partner with the service. Both flows are built to qualify and capture leads rather than just answer queries. For internal operations, the team built two AI-driven workflow automations, one covering the customer onboarding sequence and one handling medication support requests, reducing the manual workload on clinical specialists. The initial builds went from scoping to working prototype within the first week of development, followed by a testing and iteration phase before production deployment. The team has continued in an active development and support capacity since launch.
Quantus-Technik, a high-end CNC machine tools company based in Pune, India, was running key business operations across disconnected manual processes. Departments lacked visibility into each other's workflows, approvals lacked a structured tracking system, and operational data was scattered making it difficult for leadership to track performance or make timely decisions. SDLC Corp deployed a 6–10 person team to design and implement a fully configured ERP system to the company's manufacturing and sales operations. The engagement covered requirement gathering, workflow analysis, ERP module configuration, user role setup, and complete data migration. Alongside the ERP build, the team developed AI-powered automation features to surface business insights and reporting directly within the system. A custom chatbot was integrated to handle internal support queries and reduce the load on team members for routine information requests. Post-launch support and workflow optimisation were included to ensure full adoption. Within five months, 70–75% of the company's key workflows were centralised into a single system. Manual tracking dependency dropped by 40%. The integrated chatbot reduced repeated internal support requests by 30%. Leadership gained faster access to operational data and cross-department coordination improved measurably. The project was delivered on time across all milestones, rated 5.0 for schedule adherence and willingness to refer.
Transworld Logistics handled more than 2,000 invoices daily from suppliers using different invoice formats. Manual data entry caused errors and delayed approvals, with processing taking up to 48 hours. The project focused on shortening this cycle and improving the accuracy of invoice data sent to the ERP. SDLC Corp analyzed the existing workflow and built an AI document processing platform to automate invoice extraction and validation. The solution combines optical character recognition (OCR) with computer vision to identify invoice fields and capture tables across varying supplier layouts. Confidence scoring flags uncertain values for staff review, while APIs transfer validated data to the ERP in structured JSON format. A side-by-side review interface allows staff to compare extracted information with the original invoice and resolve discrepancies before approval. The platform also includes role-based access and ERP synchronization tracking. Dashboards give administrators visibility into processing volumes, exceptions, and synchronization status, helping them identify invoices that need attention. Following implementation, invoice processing time decreased from 48 hours to 4 hours. Data-entry errors fell from 4–5% to 0.1%, while the cost per invoice decreased from $2.50 to $0.45.
KISS USA needed ongoing engineering support for an Odoo retail platform covering checkout, inventory, employee processes, promotions, loyalty, SAP synchronization, and Elavon payments. The challenge was to address changing business requirements and production issues while retaining a detailed understanding of the platform’s custom modules and integrations. SDLC Corp provided a 12-member, full-time team combining Odoo development, functional consulting, project management, and solution architecture. The team enhanced and maintained custom modules, investigated production issues, resolved defects, and supported workflows connecting Odoo with SAP and Elavon payment processing. Work was organized through backlog planning, code reviews, functional and regression testing, and release coordination. Each change required attention to existing workflows and dependencies across checkout and back-office operations. Keeping a dedicated team involved preserved technical knowledge across development cycles and helped engineers investigate issues within the context of the wider platform. During an engagement lasting more than one year, SDLC Corp completed over 1,000 engineering work items, including bug fixes, production issue resolutions, functionality enhancements, and workflow improvements. Development and support remain ongoing, providing KISS USA with a consistent team to maintain the platform and deliver further changes as operational requirements evolve.
SDLC Corp implemented its own Praxis AI LMS for Fabeminds to manage mental wellness and counselor training programs. The objective was to bring training content, user access, and completion records into one platform and make learner progress easier to track. The team mapped training workflows, developed responsive dashboards for administrators and learners, and tested user permissions and course completion processes before deployment. The platform supports role-based access, course modules, learning paths, batch assignments, recorded sessions, and supporting learning resources. Centralized progress tracking and certification records help administrators monitor learning activity and review training completion. The implementation was completed in 32 weeks. Reported outcomes included 250+ learners onboarded across 12 training programs and 180+ certificate-ready records centralized. The time required to set up administrative access decreased from six hours to under one hour, while new program setup time fell from four weeks to five days.
SDLC Corp implemented an AI assistant within InnCentral, its own hotel management software, to help hotel teams find operational information, review performance and prepare guest responses. The objective was to make everyday tasks easier by reducing the need to search through several reports for routine information. The assistant uses live hotel data to answer staff questions in everyday language. Owners and hotel teams can ask about pending arrivals, occupancy, room readiness and demand trends. Conversational AI supports these interactions, while AI summarization provides concise overviews of occupancy, revenue and booking-channel performance. Staff can also use the assistant to prepare draft replies to guest enquiries, including early check-in requests. This combines access to operational information with AI-assisted writing within InnCentral. Hotel teams can review current information, request performance summaries and prepare guest communications through the same assistant.
liladhar Pasoo’s staff spent 3–4 hours each day opening, reading, and forwarding invoice emails. Incorrect routing and missed invoices delayed processing, while administrators had limited visibility into failures. The project focused on reducing manual handling, routing invoices consistently, and making processing issues easier to investigate and resolve. SDLC Corp developed an AI-assisted invoice processing system that combines document data extraction with automated email routing. The system checks the inbox every 15 minutes, filters messages by sender and subject, and extracts stock keeping unit (SKU) codes from invoice attachments. It then matches these codes against configured routing rules and forwards each email to the appropriate team. A secure admin panel allows administrators to manage SKUs, update recipient mappings, and change routing rules. Timestamped logs record processing activity, while failure alerts identify emails that need attention. Administrators can review unsuccessful attempts and retry processing with a single click. The implementation used Node.js, Python, Odoo, IMAP, Gmail and Outlook APIs, PostgreSQL, MongoDB, cron scheduling, and queue workers to support inbox connectivity, scheduled processing, data storage, and routing. Delivered within 6-7 months, the system gave administrators a central interface for managing invoice email processing. The case study reports a 90% reduction in manual effort, with more than 500 invoices processed monthly.
SDLC Corp implemented InnCentral, its own hotel management software, to bring reservations, housekeeping, billing and reporting into a single system. The project focused on simplifying daily hotel operations and giving staff a shared view of bookings, room readiness and guest accounts. The team configured room settings, rate plans, reservation workflows, housekeeping tasks, invoicing and payment tracking. An easy-to-use dashboard helps staff coordinate daily work. The platform supports role-based permissions, maintenance task management, direct bookings with live availability and reporting across multiple properties. It also provides documented support for integration with Odoo and custom ERP systems. The technology stack includes React.js, Node.js, Express.js, REST APIs, PostgreSQL and MySQL, with Stripe and Razorpay supporting payment processing. Internal workflow tracking across the overall implementation indicated 40% faster front desk coordination, 35% faster housekeeping updates and 30% less manual reporting work.
Businesses often spend hours gathering Odoo data, exporting spreadsheets, and preparing reports. SDLC Corp developed AI Dashboard Ninja to help teams review current business data directly inside Odoo, making routine reporting easier to manage. The module brings sales, CRM, finance, inventory, purchasing, project, and HR data into dashboards with KPI tiles, charts, and lists. Users can choose from eight ready-made templates or create custom views using fields, measures, and filters. They can also open the Odoo records behind each metric to check the details. An AI-assisted builder turns plain-language requests into dashboard widgets, which users can review before use. Dashboard sharing follows Odoo roles, record rules, and company permissions, keeping reporting access consistent with existing controls. Built for Odoo 18.0 and 19.0 using Python, the Odoo ORM, JavaScript, and Gemini API integration, the product helps teams monitor live KPIs and adjust routine reports without developer support. It reduces the need to repeatedly assemble spreadsheet updates and keeps business reviews closer to the source data.
Fillingaro needed to connect its DigiBahi platform with Tally accounting operations. The goal was to extract information from scanned documents and export that data to the Tally server and the client’s Tally environment. SDLC Corp began working with Fillingaro in August 2025, developing the document scanning, AI data extraction, and Tally integration workflow for DigiBahi. The scope covers retrieving information from documents, preparing extracted data for export, and handling the Tally operations required to transfer it into the accounting system. A central technical challenge has been managing data retrieval and export across server and client setups. The work requires connecting the extraction process with the receiving Tally environment so that information captured from documents can be used in accounting operations. The platform supports e-Way Bill creation with pre-filled details, PDF sharing, and live vehicle route tracking. More than 35 business reports provide access to profit and loss statements, balance sheets, inventory, and payment aging details from synced books. DigiBahi’s mobile accounting features help users record sales and expenses, create vouchers and quotations, review ledgers, and track receivables and payables. Desktop accounting sync keeps business records connected, while automatic SMS and email reminders help teams follow up on outstanding payments. Users can also share payment reminders and ledger statements through WhatsApp. The project remains ongoing, with SDLC Corp continuing development on DigiBahi’s document processing workflow and addressing the data-fetching and Tally integration requirements.
SDLC Corp developed StafFolder, a care documentation platform with an AI Document Generation Assistant, to help care teams prepare documents using information already stored in client records. The project focused on reducing repetitive data entry while keeping responsibility for documentation with authorised care professionals. The client needed a consistent way to prepare person-centred care plans, risk assessments and related reviews. The objective was to reuse recorded information about each person’s health, preferences and support needs, giving staff a structured starting point for documentation. SDLC Corp’s work covered platform development and AI implementation within the care documentation workflow. The assistant is designed to draw on client profiles, medical conditions, medication, allergies, mobility and communication needs, alongside previous care records. Its scope includes client summaries, support plans, risk assessments and review documents. Care plan drafts cover personal goals and practical support instructions. Risk assessment drafts address hazards, warning signs, control measures and escalation actions. Review workflows are designed to compare previous and current information, highlight changes and suggest updates for staff to assess. Every AI-generated draft requires human review and approval before becoming part of the permanent client record. The workflow includes options to regenerate drafts, improve wording, rewrite sections, edit content, accept it or reject it. The project brings AI-assisted drafting into StafFolder’s care documentation process, with the aim of reducing repeated preparation work while preserving professional judgement and control over final records.
Port of Fujairah needed a clearer way to manage vessel requests, review anchorage availability, and coordinate vessel movements. Information was spread across separate records, calls, and emails, making it difficult for port teams to maintain a shared view of daily operations. SDLC Corp built a centralized Anchorage Management System (AMS) connecting vessel requests, vessel information, anchorage allocation, monitoring, alerts, and operational history. Operators can review available, occupied, reserved, and restricted anchorage areas before confirming an assignment. The system keeps allocation decisions with port operators while bringing the supporting information into one workflow. The platform’s documented technology stack includes React, TypeScript, Node.js, REST APIs, WebSockets, PostgreSQL, and PostGIS, alongside GIS mapping and maritime data integration capabilities. The AI development scope covers vessel anomaly detection and ETA/ETD prediction. The planned anomaly detection model will use real-time Automatic Identification System (AIS) data and historical vessel behaviour to identify unusual movements, unexpected speed changes, route deviations, AIS data irregularities, and potential restricted-area violations. These findings are intended to support timely alerts and help operators review activities that need attention. LightGBM is planned for predicting vessel Estimated Time of Arrival (ETA) and Estimated Time of Departure (ETD). Model inputs will include historical AIS records, vessel characteristics, speed, position, weather conditions, anchorage occupancy, and operational history. The predictions are intended to support anchorage allocation, vessel scheduling, capacity forecasting, and operational planning. The core AMS provides a shared workflow for vessel and anchorage information. The AI scope extends this work toward predictive monitoring and planning support. Model accuracy will be validated using historical Port of Fujairah data before deployment. Reduced vessel waiting times and improved resource utilization remain project objectives, with measured AI outcomes pending validation.
DYD wanted customers to see how furniture would look in their own rooms before buying it. The challenge was to keep products in proportion to the space and allow furniture businesses to use items from their own catalogs. SDLC Corp built the application, including room measurement, AI rendering, testing, and deployment. Users can upload a room photo, remove unwanted items, and try different furniture arrangements. They can also change wall finishes, flooring, and lighting without creating a room model manually. The application uses Vue.js, Python, and Django, with ComfyUI and Flux supporting the rendering workflow. For businesses, SDLC Corp added catalog management, customer records, dashboards, and separate access for designers and staff. The team also built usage-based billing, shareable room previews, and a widget that businesses can place on their websites. Customers can download their finished visualization or continue to the product purchase.