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Inhuren As a trusted technology partner with 93% recurring clients, we deliver custom face recognition software development services to empower businesses globally with rock-solid, scalable, and cost-efficient biometric AI solutions.
As a trusted technology partner with 93% recurring clients, we deliver custom face recognition software development services to empower businesses globally with rock-solid, scalable, and cost-efficient biometric AI solutions.
While poor lighting and deepfakes break standard systems, modern regulations often demand resilient biometrics to be on top of vulnerable passwords. We solve these identity challenges to eliminate business risks and prevent financial losses.
Our team blocks spoofing via masks, photos, and deepfakes using liveness detection to protect your business from severe financial losses caused by corporate account takeovers.
Our custom solutions reduce customer drop-offs caused by lengthy KYC workflows and help instantly verify user identities to accelerate onboarding and boost conversion rates.
Our engineers clear facility bottlenecks by augmenting or replacing your existing magnetic card readers and PIN-based entry with instantaneous, frictionless biometric scanning.
We seamlessly integrate advanced AI models and deep learning pipelines directly into your old-hat CCTV camera networks for a smooth system upgrade with minimal operational disruption.
Our system architects implement rigorous encryption algorithms and vector hashing to help you meet complex regulatory requirements, including GDPR, HIPAA, and other regional or industry-specific compliance obligations.
We deploy advanced Re-ID models to accurately track individual movement paths, which gives you complete visibility into customer behavior patterns and attendance in real time.
At Innowise, we build custom facial recognition systems tailored to your needs. Our AI pipelines ensure low latency (less than 200 milliseconds) and 80-95% accuracy for identity verification, access control, and fraud prevention.
Choosing the best solution architecture for your organization will depend on a number of factors, such as latency, data security, and network throughput. Because of this, we always build solid deployment models designed specifically for your business environment.
We have our CNN inference models deployed directly on edge cameras and GPUs, which allows for immediate image verification with no network latency in air-gapped or secure locations.
We deploy our recognition pipeline on AWS EC2 and EKS clusters that allow for the processing of thousands of concurrent video streams with auto-scaling and 99.9% uptime.
We run lightweight face detection on the edge nodes to allow for faster processing while offloading the ArcFace embedding matching to the cloud GPU in order to balance speed and costs associated with multi-site deployments.
We make the recognition of a person available through REST and gRPC APIs, your team can add facial identification to any application without having to re-architect existing systems.
We create SDKs for both iOS and Android with built-in biometric login via FaceID, along with custom extraction of facial embeddings, so end users can authenticate securely while offline.
We architect fault-tolerant microservices using AWS Kinesis & Kubernetes that can handle burst traffic from dozens of live cameras with no delay or degradation of services.
Stop it with a custom face recognition software development company.
Every system we develop is built upon a Zero Trust Architecture foundation, with rigorous biometric data protection guidelines implemented from the first code line to production deployment.
We establish project teams within 1-2 weeks and follow a structured build process that has been stress-tested in real-world environments, like poor lighting, motion blur, and messy video feeds.
Stronger security against fraud
Faster verification, better conversions
Accuracy that holds in real conditions
Automated ID checks at scale
Advanced liveness detection and 3D depth mapping provide reliable hardware-level protection from presentation attacks, including silicone masks, printed photos, and deepfake videos, therefore providing a reduction of security incidents by 25-50%.
With over 19 years of technical experience in hundreds of successful AI-driven projects, we provide only accredited architects, substantial real-world testing, and transparent delivery from day one of the project.
We have a staff of more than 100 technology consultants and ML experts, who are AWS certified, with extensive experience creating and deploying production-grade machine learning models that leverage deep learning and real-time computer vision.
We have successfully delivered over 15 biometric AI projects, and we maintain global development centres with flexible hours of operation in order to meet client deadlines.
Our expertise spans the breadth of industries such as retail, finance, healthcare, logistics, and many more, and our domain knowledge ensures seamless biometric integrations across all those sectors.
All systems we create meet HIPAA, GDPR, and CCPA compliance, and are backed by ISO-certified security practices, AWS-certified architects, and regular third-party security audit cycles.
We hire only the top 5% of engineers, and 85% of our specialists are at the middle or senior levels of expertise, so your project gets people who have previously solved these types of challenges in development.
We will work closely with you, integrating into your current processes, tools, and sprint cycles with complete visibility and no surprises, so everything that you see is related to the scope of the project and will be built, tested, and delivered according to the project deadline.
Innowise heeft een geweldige applicatie gebouwd vanuit het niets in een verbazingwekkend korte tijd van slechts ongeveer 3 weken. Hun senioriteit en diepgaande ervaring op dit gebied maken hen tot waardevolle partners.
Innowise vond voortdurend efficiënte oplossingen voor de uitdagingen. De middelen waren zeer behulpzaam en communicatief, en ze gaven blijk van een indrukwekkende vastberadenheid en gretigheid om problemen op te lossen.
Het werk van Innowise voldeed aan alle verwachtingen. Het team was efficiënt en snel en zat bovenop hun projectresultaten. Klanten kunnen een ervaren team verwachten dat een scala aan zakelijke diensten aanbiedt.
Pricing depends on the complexity of liveness detection algorithms and your chosen cloud or edge infrastructure. An accurate estimate will be provided at no cost after an initial investigation of your CCTV systems and business requirements.
Typically, deploying a new model will take between 2-4 months. But you'll probably find that there is also some additional time required for batch processing pipeline configuration, as well as older systems integrations.
Yes, we use specialized CNN architectures (with extensive training on a variety of different complex datasets) to achieve stable detection in low-light situations, in shadows, and at night.
To avoid data leaks, we use a match-on-device approach and an irreversible method of hashing facial imagery. For compliance with GDPR and HIPAA, every face image is encrypted.
Yes, we can make custom APIs in REST/GPRC formats to integrate our biometric algorithms seamlessly into your current ecosystem without disrupting your daily operations.
On average, we provide more than 95% accurate real-time video (using high-quality inputs) with less than 200 ms of delay. Even if the video is taken in bad lighting or from unusual perspectives, our models will still deliver an exceptionally good recognition rate between 85-90%.
There are global data privacy laws that require both: (a) a user’s explicit consent to collect and process their personal data, and (b) transparency in how personal data has been collected, processed, and shared. We incorporate a “privacy by design” approach directly into your systems and applications.
Our vector database architecture allows for horizontal scaling for millions of face embeddings without degrading accuracy. We leverage indexed nearest neighbor search and AWS auto-scaling to ensure 1:N matches are performed quickly as the identity database grows.
