CyborgIntell is an AI & Machine Learning product company. Our next-generation Automated Machine Learning (AutoML) platform self-learns, mines, predicts, and scores events in real-time. Built by data science industry veterans, our core strengths come with data science rigor and expertise in our business verticals. Our AutoML platform augments the data science team's capability manifold, enabling them to be faster, consistent, accurate, and focused on solving business problems rather than coding. This expands the employable talent pool while transforming ‘Data Science’ practice as a sustainable organizational capability. This, we consider as the next phase of Data Science evolution. VALUE PROPOSITION & USP – ZERO CODE, Single & Seamless Platform to Develop, Deploy, Manage & Govern all ML models across Enterprise Functions ● Scalable AI - Develop, deploy and operationalize 1000’s of complex ML models and move it into production in few hours ● Decision AI - Automated multiple decision rules and policies in real time on the fly ● Actionable AI - Ability to do AI based recommendation at customer level to make decision instantly ● Integrated AI - Ability to integrate multiple AI models to solve complex business problems across enterprise functions ● Governance AI – Auto documentation, Audit data, code, algorithms. Govern models by creating approval hierarchy and bring accountability for responsible usage of AI ● Model Risk Management – Make business decisions with high degree of confidence with ‘MRM’ – Early warning indicators for model degradation, measure drift, auto retrain and self-learning to constantly improve accuracy.
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CyborgIntell (CI) is an enterprise AI software company which automates the entire lifecycle of Data Science and Machine learning, to accelerate the data to decision cycles for businesses. Our flagship product “iTuring”, is NO CODE AI driven Data Science and Machine Learning software that enables enterprises to Develop, Deploy, Operationalize and Manage risk of sophisticated Machine Learning models seamlessly on a single platform. iTuring is a platform for everyone –expert data scientist, business leader and problem solver and accelerates the advancement and utilization of data driven solutions with complete transparency and explainability. iTuring has been exclusively designed for Financial Services with governance, audit ready documentation available, governance mechanism for responsible use of AI.
591, 15th Cross Rd, Sector 4, HSR Layout, Bengaluru, Karnataka 560102
BENGALURU, Karnataka 560034, IN
Dallas–Fort Worth Metroplex, Texas 75006, US
CyborgIntell Africa Office 9, WorkCentral Bellairs Centre Bellairs Drive & Malibongwe Drive Northriding Johannesburg, 2153 South Africa
Johannesburg, South Africa 2153, ZA
CyborgIntell reposted this
🎄 Merry Christmas from all of us at CyborgIntell! 🎄 To our valued clients, partners and team members: May your Christmas be filled with peace and joy. We are incredibly grateful for your support and collaboration throughout the year. Let’s continue to spread the spirit of giving and kindness that makes this holiday season so special. Warm wishes!
🎄 Merry Christmas from all of us at CyborgIntell! 🎄 To our valued clients, partners and team members: May your Christmas be filled with peace and joy. We are incredibly grateful for your support and collaboration throughout the year. Let’s continue to spread the spirit of giving and kindness that makes this holiday season so special. Warm wishes!
💡Did you know: Up to 30% of insurance claims are embellished, leading to billions in unnecessary payouts annually? This highlights a critical need for AI-driven Fraud, Waste, and Abuse (FWA) Detection in the insurance sector. 🔍 Imagine an AI system that: 1. Flags anomalies in claims data based on historical patterns. 2. Identifies suspicious behavior, such as repeated claims from specific geographies. 3. Integrates seamlessly with existing workflows to minimize false positives and support investigators. 💰 The result? 1. Faster claims processing 2. Reduced payouts for fraudulent claims 3. Increased trust between insurers and their customers. At CyborgIntell, we’re working on solutions that empower insurers to stay one step ahead of fraud while delivering seamless experiences to honest policyholders. What do you think will be the biggest game-changer in insurance FWA detection over the next few years? #insurance #Claims #Frauddetection #Lending #insurtech #FWA
" PyTorch, Python, Explainable AI, Machine Learning, Deep Learning, NLP, LLM & Transformers, SQL, Cobol, Fair Lending, llama Index, Langsmith, Langchain, DSPy, RAG, Core Java, J2EE, Spring, Jersey, MySQL, Hadoop, C, C++, C#, Spark, Scala, ETL frameworks, Statistical Modeling & Probability, Big Data" The above list of Skill Sets along with Core Competencies like "Problem Solving, Design & Architecture, Business Acumen, Domain Expertise and Interpersonal Skills" were the answers we received from our Technical team when we asked them what it is - that makes them valuable in the organization. Today, let’s take a moment to recognize and celebrate MEN for more than just their resumes or professional skills. Men are leaders, caregivers, mentors, partners, dreamers, achievers, go-getters and so much more. In the tech world, it's easy to focus on core competencies—but let's not forget the human side. The strength to lead with empathy, the courage to admit mistakes, the passion to mentor others, and the humility to learn are what truly make a difference in our workplaces and communities. To all the men out there: Thank You for showing up as your full, authentic selves—beyond the code, beyond the KPIs, and beyond the job titles. Here’s to redefining success and masculinity in ways that make the world a better, more inclusive place. 💙 🌍 Happy International Men's Day! 🎉 What does International Men's Day mean to you? Let’s celebrate together in the comments! #InternationalMensDay #Diversity #HumanSideOfTech #CelebrateMen
Closing the CREDIT TAPS after economic or market conditions become unfavorable...? When credit managers delay tightening lending conditions, the consequences can be severe for both lenders and the broader economy. Here’s a breakdown: 1. Increased Credit Losses When credit managers fail to tighten credit early, they often continue lending to borrowers who are increasingly at risk of default due to worsening economic conditions (e.g., rising unemployment, inflation, or falling asset values). If borrowers cannot repay, lenders face increased non-performing loans (NPLs) and write-offs. This can significantly erode profitability and capital reserves. 2. Overexposure to Risky Borrowers By continuing to issue credit during a period of declining economic resilience, lenders end up with an eroded portfolio containing higher proportions of risky loans. 3. Damage to Market Liquidity When credit managers suddenly "close the taps," businesses and consumers lose access to necessary liquidity for operations and spending. This abrupt credit contraction exacerbates economic downturns, increased bankruptcies, foreclosures, and unemployment. Businesses that rely on short-term credit to manage cash flow might fail to pay employees or suppliers, leading to a string of ripple effects. 4. Loss of Borrower Confidence A sharp pivot from easy credit to restrictive lending creates uncertainty among borrowers hindering normal spending patterns. Lenders that tighten too late may be seen as reactive and unreliable, losing trust from businesses and consumers. 5. Fewer Options for Mitigation When credit managers act late, they miss the chance to introduce measures like restructuring loans, tightening standards, or adjusting terms for at-risk borrowers. Early action can mitigate losses and reduce the need for drastic measures later. Solution: Leveraging Predictive Analytics equipped with Advanced AI/ML platforms can help identify risks early, allowing for timely data-driven personalized credit management that aligns with both financial and customer-oriented goals. Being better prepared can prevent higher losses and a weakened economy resulting in shorter recovery period. This can protect the lending institutions as well as the broader economic ecosystem. #CreditRisk #LendingSolutions #CreditManagement #FutureofLending #CreditDecisioning #DigitalLending #AIinFinance #DataDrivenDecisions Suman Kumar Singh Srivalsan Ponnachath Bryan McLachlan Vipin Johnson Tarika Bhutani Martin L. Litabe Devina Kumar Aishwarya Hegde
🎉 Happy Children's Day from the CyborgIntell family! 🎉 Today, we’re taking a trip down memory lane and celebrating the childlike wonder in all of us. Can you guess who’s who in this adorable collage of our team members' childhood photos? 😍 Drop your guesses in the comments below with the grid number and the name, and let's see who knows our team best! 😎 Let’s celebrate the joy, curiosity, and laughter that children bring to our lives— and remember that a playful spirit can drive innovation and creativity at any age. 🤩 #ChildrensDay #GuessWho #ThrowbackChallenge #CyborgIntellFun #EngagementPost
🔍 Tackling the Thin-File Borrower Problem in Credit Decisioning with fully automated Data-to-Decision DSML AI platform 🔍 In Credit Decisioning, one of the biggest challenges is accurately assessing "thin-file" borrowers—individuals with limited or no traditional credit history. Think of young professionals, freelancers, or people new to a country. How can financial institutions assess the creditworthiness of these applicants with minimal historical data? Here’s where a Data Science and Machine Learning (DSML) platform can make all the difference: ✨ Alternative Data Sources: DSML platforms can pull in non-traditional data points, like utility payments, mobile phone usage, or even social media behavior, to build a broader profile. This data helps paint a picture of financial habits and reliability where traditional scores fall short. ✨ Anomaly Detection: By using machine learning models that identify patterns and anomalies, DSML platforms help spot irregular behavior that might signify credit risk. For instance, sudden changes in spending habits or patterns in bill payment frequency can provide insights into stability and reliability. ✨ Real-Time Decisioning: With APIs, credit decision models can process new data immediately, making credit approvals almost instantaneous. Thin-file borrowers get a quick decision without the hurdles of traditional scoring systems. ✨ Bias Mitigation: DSML platforms allow us to monitor for biases and correct them, ensuring that alternative data-driven decisions remain fair and equitable. This capability builds trust and widens access to credit. 📈 What do you think? Are alternative data points the future of inclusive credit decisioning? Would love to hear your thoughts! Get in touch for a demo of CyborgIntell's #DSML platform #iTuring to see AI/ML in action: https://lnkd.in/gyPq-Pyy https://lnkd.in/gTfxtJYd #CreditDecisioning #MachineLearning #AI #Fintech #BFSI #AIMLmodels #demo #creditassessment
CyborgIntell reposted this
Now that we are meeting with clients, partners and potential clients in so many countries across the globe (+-30 at last count) a growing topic of conversation around AI is risk management, regulation and potential regulation, and resulting compliance challenges. This trend is particularly true with banks, insurers and lenders. We come across organizations who have operationalized +- 1000 AI/ML models that they know of (we suspect, based on experience, there probably many more - especially if those running at vendors and partners are included). How can these organizations be sure that every model is performing optimally, is transparent, fair, ethical and without bias. In addition are these models compliant with various regulations, are there version controls and audit trails and therefore clear accountability. If all of these are in place, can they be easily proved to risk committees, regulators and auditors? It is for all of these reasons, and also so that organizations can trust extensive use of AI, that CyborgIntell has built our Model Risk Management capability on our AI/ML platform. We believe that real-time explainability at both a model and a decision level, transparency, auto-documentation, version control, inventory, tracking, reporting and audit trails are essential. In addition there is comprehensive functionality to save time, money and reduce risk. Some of this includes automatic real-time measurement of scores of KPAs, with notifications of model or data drift, root cause analysis in minutes, champion challenger capability to test performance of existing models. Use of AI/ML is only going to intensify - we recommend that organizations implement best practices around risk and compliance as early as possible.