Appinventiv
Global 1,600+ engineer firm delivering mobile-first ML solutions across five continents.
Founded 2015 | Noida, India | 1,600+ employees
custom-mlgenerative-ainlpcomputer-visionml-consultingpredictive-analytics
What is Appinventiv?
Appinventiv is a global digital innovation and mobile app development company founded in 2015 and headquartered in Noida, India. The company has grown to 1,600+ technology experts with offices in the US, UAE, Australia, and the UK, and has delivered 1,000+ digital assets for 3,000+ businesses worldwide. Appinventiv's ML practice focuses on mobile-first AI integration — embedding machine learning into iOS, Android, and cross-platform mobile products alongside web and enterprise applications.
Appinventiv was founded in 2015 and is headquartered in Noida, India. The firm employs 1,600+ people and works primarily with clients in healthcare, retail, fintech, logistics, SaaS sectors. Its primary differentiator is: 1,600+ specialists with a mobile-first AI approach and global footprint delivering 1,000+ digital assets with embedded ML — strong for consumer-facing AI product work.
Appinventiv tech stack and services
TensorFlowPyTorchOpenAIAWSAzureGCPPythonReact NativeFlutterSwiftKotlin
| Service area |
|---|
| Custom ML Development |
| Generative AI |
| NLP |
| Computer Vision |
| ML Consulting |
| Predictive Analytics |
Appinventiv use cases
Short answer: Appinventiv is best suited for global businesses, mobile-first ML, five-continent delivery.
| Use case |
|---|
| Mobile AI feature development for iOS/Android apps requiring on-device ML inference |
| Computer vision integration for mobile retail, fitness, or healthcare applications |
| NLP chatbot and virtual assistant integration into mobile consumer products |
| Generative AI feature development for consumer-facing SaaS or fintech mobile products |
| Custom ML development for logistics or supply chain mobile applications |
Appinventiv pricing
Short answer: Appinventiv uses a fixed project, dedicated team, t&m pricing approach. Minimum engagement starts at $15K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $15K | Well-defined scope |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
| T&M | Variable; depends on team size | Large programmes or team augmentation |
Appinventiv does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
Appinventiv pros and cons
| Advantages | Things to consider |
|---|---|
| +1,000+ digital asset delivery track record across consumer-facing ML products | -India-based primary delivery introduces time zone complexity for US East Coast teams |
| +Mobile-first ML capability enables on-device AI integration in iOS and Android applications | -Mobile-first orientation means less enterprise MLOps and data engineering depth |
| +Accessible minimum engagement ($15K) relative to global team size | -Generalist digital product firm — ML is one of many specializations, not the sole focus |
| +Offices on five continents supporting enterprise clients across North America, EMEA, and APAC | |
| +Computer vision and NLP integration into mobile products is a genuinely differentiated capability |
Appinventiv vs alternatives
How Appinventiv compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Dedicated ML boutique, strategy through production MLOps. | ML-only focus with a dedicated specialist team backed by 25 years of the parent company software delivery infrastructure — unusually deep for a firm of this size | 4.8 | Full comparison |
| LeewayHertz | Enterprises, end-to-end AI delivery, Fortune 500 clients. | Product-centric AI delivery culture with verified Fortune 500 client references including ESPN, Siemens, and 3M — now operating within The Hackett Group | 4.0 | Full comparison |
| InData Labs | Mid-market orgs, complex ML, deep data-science expertise. | Pure-play ML boutique with a measurably higher specialist-to-generalist ratio than typical service firms, confirmed by Clutch as a top AI service provider | 4.5 | Full comparison |
| HatchWorks AI | Companies wanting AI-native, generative-AI-embedded delivery. | Clutch #1 AI Services Company with a proprietary Generative Driven Development methodology claimed to reduce delivery time by 30–50% (per company website; independently unverifiable) | 4.4 | Full comparison |
| STX Next | Orgs needing ML operationalized in Python-native systems. | Europe's largest Python-specialist firm uniquely positioned to embed ML into production software without the integration friction that plagues pure-play ML boutiques | 4.3 | Full comparison |
| Tredence | Enterprises, last-mile ML adoption, supply chain and retail. | Industry-specific AI accelerators and a proven focus on last-mile ML adoption, closing the execution gap between data science output and real business value | 4.3 | Full comparison |
| Addepto | Finance, energy, retail — bespoke ML with pipeline... | End-to-end AI/ML delivery with particular sector depth in financial services and energy — industries that require compliance sophistication alongside technical capability | 4.2 | Full comparison |
| DataForest | Data-first companies, robust engineering foundation for ML. | Data engineering-first approach builds pipeline and data quality foundations before model development, addressing the root cause of most ML project failures | 4.2 | Full comparison |
| Forte Group | Orgs wanting Tier-1 rigor, specialist agility, roadmap to... | Structured AI service lines with Tier 1 delivery rigor and specialist consultancy agility — serving organizations that need both without enterprise-tier pricing | 4.1 | Full comparison |
| Binariks | Healthcare, fintech, insurance — compliance-first ML engineering. | Compliance-first ML engineering for regulated industries — governance and audit trails are built in from the architecture stage, not retrofitted after launch | 4.1 | Full comparison |
| Softeq | Hardware and industrial companies, edge ML on embedded... | Unique capability to combine hardware design expertise with ML engineering, deploying models at the edge where cloud-only ML firms cannot operate | 4.1 | Full comparison |
| Markovate | Retail, travel, fitness — recommendation engines, 300+ projects. | 300+ delivered projects spanning recommendation systems, computer vision, and dynamic pricing, with deeper consumer-facing ML specialization than most comparably sized firms | 4.0 | Full comparison |
| ScienceSoft | Established enterprises, 35+ years, stable US vendor. | 35+ years of enterprise delivery experience with a mature ML practice — providing compliance readiness, institutional knowledge, and process maturity rare in younger ML-focused competitors | 4.0 | Full comparison |
| Miquido | Product teams, ML in polished products, Google-certified. | Google-certified AI/ML capability paired with strong product design — clients receive ML that works inside well-crafted user experiences, not bolted-on algorithms | 4.0 | Full comparison |
| Simform | Industrial and enterprise, cloud-native AWS ML at scale. | AWS Premier Partner with 1,000+ engineers and documented depth in industrial IoT ML — connecting physical sensor streams to cloud ML inference at production scale | 3.9 | Full comparison |
| Intuz | SMBs, fixed-price discovery, 1,700+ projects. | 1,700+ project track record with a discovery-first engagement model making enterprise-grade ML accessible to SMBs through risk-reduced fixed-price POC phases | 3.9 | Full comparison |
| Scopic | Orgs wanting custom ML, 20+ years, strong computer... | 20+ years as a distributed software company gives Scopic strong custom ML engineering discipline with confirmed production deployments across transportation and healthcare | 3.9 | Full comparison |
| N-iX | Enterprises, large-scale Eastern-Europe ML engineering capacity. | 2,400+ engineers with deep specialization in scalable AI architectures, able to field large dedicated teams for complex multi-year ML programmes at competitive Eastern European rates | 3.9 | Full comparison |
| Oxagile | Media, AdTech, sports — video ML, 20+ years... | 20+ years of video domain expertise uniquely positions Oxagile for ML use cases involving video understanding, visual search, and real-time video analytics | 3.8 | Full comparison |
| Innowise | Banking, agriculture, healthcare — compliance-aware ML. | Cross-vertical ML delivery with documented case studies in banking automation, agricultural forecasting, and healthcare diagnostics — unusual breadth across regulated industries | 3.9 | Full comparison |
| Intellectsoft | Fintech, healthcare, construction — ML in enterprise ecosystems. | Palo Alto HQ with 10 global delivery offices combining US-based account management with competitive Eastern European delivery rates for enterprise ML programmes | 3.8 | Full comparison |
| DataRoot Labs | Startups and scale-ups, AI strategy plus execution, accessible. | One of Ukraine's most recognized ML consultancies — combining strategy-level AI advisory with hands-on engineering, a combination rare at this team size and price point | 3.8 | Full comparison |
| Itransition | Enterprises, ML in legacy systems, 25+ years delivery. | 25+ years of enterprise software delivery with five dedicated R&D labs, giving clients a mature delivery operation with advanced ML research support at competitive rates | 3.9 | Full comparison |
| 10Pearls | US enterprises and government contractors, AI-native, LATAM delivery. | AI-native engineering culture with four CRN Solution Provider 500 recognitions and 1,400+ experts spanning North America and LATAM for enterprise AI programmes | 3.8 | Full comparison |
| Coherent Solutions | Microsoft-stack enterprises, #1 Twin Cities IT firm. | Ranked #1 IT consulting firm in the Twin Cities five times in six years with 2,000+ engineers across 10 development centers, offering enterprise ML at competitive rates | 3.8 | Full comparison |
| Iflexion | US orgs, ML within custom enterprise software systems. | 25 years of enterprise software delivery with 850+ professionals embedding ML into complete systems rather than delivering standalone models that require separate integration work | 3.7 | Full comparison |
| Avenga | Telco, banking, automotive enterprises — 6,000+ engineer scale. | 6,000+ specialists across 44 delivery centers formed through PE-backed acquisitions, providing enterprise-scale AI delivery capacity — though cultural integration across legacy entities is ongoing | 3.7 | Full comparison |
| BairesDev | Companies wanting rapid ML scale-up, LATAM nearshore, US... | 4,000+ ML-capable LATAM engineers in US time zones with 1,200+ completed projects, enabling rapid scale-up for organizations that need to grow their ML capacity fast | 3.7 | Full comparison |
| Turing | Teams needing pre-vetted senior ML developers, staff augmentation. | AI-powered vetting platform screening 3M+ global ML developers to place the top 1% directly in client engineering teams at rates competitive with US in-house hiring | 3.7 | Full comparison |
| EPAM Systems | Large enterprises, Fortune 500 scale, global compliance. | 62,000+ engineers across 50+ countries delivering ML inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise AI programmes | 3.9 | Full comparison |
Appinventiv FAQ
What is Appinventiv?
Appinventiv is a global digital innovation and mobile app development company founded in 2015 and headquartered in Noida, India. The company has grown to 1,600+ technology experts with offices in the US, UAE, Australia, and the UK, and has delivered 1,000+ digital assets for 3,000+ businesses worldwide. Appinventiv's ML practice focuses on mobile-first AI integration — embedding machine learning into iOS, Android, and cross-platform mobile products alongside web and enterprise applications.
How much does Appinventiv charge?
Appinventiv uses fixed project, dedicated team, t&m pricing. Minimum engagement starts at $15K. A discovery call is required to get project-specific quotes.
What tech stack does Appinventiv use?
Appinventiv works with TensorFlow, PyTorch, OpenAI, AWS, Azure, GCP, Python, React Native, Flutter, Swift, Kotlin. Primary industries served include healthcare, retail, fintech, logistics, SaaS.
Is Appinventiv right for enterprise?
Global businesses, mobile-first ML, five-continent delivery. 1,600+ team size. Key consideration: India-based primary delivery introduces time zone complexity for US East Coast teams.
What are the best Appinventiv alternatives?
The best alternatives to Appinventiv depend on your use case. Top options are:
- Tensorway: ml-only focus with a dedicated specialist team backed by 25 years of the parent company software delivery infrastructure — unusually deep for a firm of this size
- LeewayHertz: product-centric ai delivery culture with verified fortune 500 client references including espn, siemens, and 3m — now operating within the hackett group
- InData Labs: pure-play ml boutique with a measurably higher specialist-to-generalist ratio than typical service firms, confirmed by clutch as a top ai service provider
Compare Appinventiv with other Machine Learning Development companies
Appinventiv vs Tensorway Appinventiv vs LeewayHertz Appinventiv vs InData Labs Appinventiv vs HatchWorks AI Appinventiv vs STX Next Appinventiv vs Tredence Appinventiv vs Addepto Appinventiv vs DataForest Appinventiv vs Forte Group Appinventiv vs Binariks Appinventiv vs Softeq Appinventiv vs Markovate Appinventiv vs ScienceSoft Appinventiv vs Miquido Appinventiv vs Simform Appinventiv vs Intuz Appinventiv vs Scopic Appinventiv vs N-iX Appinventiv vs Oxagile Appinventiv vs Innowise Appinventiv vs Intellectsoft Appinventiv vs DataRoot Labs Appinventiv vs Itransition Appinventiv vs 10Pearls Appinventiv vs Coherent Solutions Appinventiv vs Iflexion Appinventiv vs Avenga Appinventiv vs BairesDev Appinventiv vs Turing Appinventiv vs EPAM Systems