We build with Keras
We use Keras to design, train, and deploy deep learning models quickly and reliably that support your business goals. From architecture prototyping and hyperparameter tuning to production deployment, we create products designed to evolve with your needs.
DISCUSS YOUR PROJECTRapid Prototyping
We prototype neural network models in days, not weeks.
Simple, Readable API
We write clear model code that stays easy to maintain.
Backend Flexibility
We run the same models on TensorFlow, PyTorch, or JAX.
BENEFITS OF KERAS technology
We use Keras to prototype models quickly, simplify neural network code, and speed up experimentation.
BUILD
[01]- Define model architectures
- Prototype rapidly
- Configure layers and training
- Reduce boilerplate code
ENGAGE
[02]- Train and evaluate models
- Visualize training with TensorBoard
- Tune hyperparameters fast
- Test ideas across use cases
GROW
[03]- Deploy with TensorFlow Serving
- Switch backends when needed
- Scale successful prototypes
- Extend to production pipelines
Our Keras Technology Stack
We combine Keras with TensorFlow, TensorBoard, and TensorFlow Serving for training, visualization, and deployment, choosing backends and tooling around your prototyping speed and production needs.
Custom Keras development company
With our Keras development services, we build and prototype deep learning models for computer vision, natural language processing, and tabular data tasks, tailored to your boldest business goals. Having years of experience with Keras and tf.keras, our engineers harness its full potential to deliver fast, readable model code across industries and company sizes. Whether it's a quick proof-of-concept or a production-ready deep learning system, we design and train models that move from experiment to deployment without unnecessary complexity. Our range of Keras development services spans consulting, model design, training, and deployment support. We work as your technical partner and ensure complete transparency and comfortable communication throughout the process, bringing deep expertise in neural network design and a pragmatic approach to experimentation and problem-solving. All this to make sure your models move quickly from idea to validated prototype, and moves your business forward.
OUR KERAS SERVICES
We build, modernize, and support Keras models around your product goals.
Your roadmap is growing faster than your team. Add senior engineering capacity and deliver more without sacrificing quality.
Rapid proof-of-concept models for computer vision, NLP, and tabular data experiments.
Structured training pipelines with hyperparameter tuning and TensorBoard visualization built in.
Deploy trained models with TensorFlow Serving for reliable, scalable production inference.
Migrate legacy deep learning code to Keras or upgrade existing models to newer backends.
Meet our Keras experts
A curated selection of senior specialists currently available for new engagements.
We Turn Technology Into Results
Partner with a team that blends technical precision, creative design, and business insight. We’ll help you launch, scale, and dominate your digital niche.
Frequently Asked Questions
Common questions about how we use Keras and what it can bring to your project. Have a specific requirement?
How does SoftDoes use Keras?
We use Keras to design, train, and evaluate neural network models for computer vision, natural language processing, and tabular data tasks. We select the backend and training setup around your product's speed and scale requirements.
What types of models do you build with Keras?
We build image classifiers, recommendation models, text classifiers, and other neural networks, ranging from quick proof-of-concept prototypes to production-ready deep learning systems.
Do you build with Keras on top of TensorFlow?
Yes. Most of our Keras work runs on tf.keras, TensorFlow's built-in implementation, which gives us access to TensorBoard for training visualization and TensorFlow Serving for deployment.
Can Keras models run on backends other than TensorFlow?
Yes. Keras 3 supports TensorFlow, PyTorch, and JAX backends, so the same model code can run on different engines depending on your team's existing infrastructure.
Can Keras integrate with our existing systems?
Yes. Keras models can be wrapped in APIs, connected to existing data pipelines, and deployed alongside your current backend services without requiring a full system rewrite.
When is Keras the right choice over a lower-level framework?
Keras fits well when you need fast iteration, readable model code, and a quick path from idea to working prototype. For highly custom architectures or fine-grained control, a lower-level framework may fit better.
How do you decide whether Keras fits a project?
We look at your data, performance requirements, team experience, and timeline, then confirm Keras is the right fit before starting model development.
