How AI Consulting Can Accelerate Business Growth
AI’s potential needs little introduction. The problem is, many organisations struggle to harness AI’s full potential due to a lack of in-house expertise, data scarcity, and uncertainty about effectively deploying AI solutions. This is where Aya Data’s AI consulting services come in. Our team of experienced data scientists, engineers, and subject matter experts work to understand your challenges and goals, providing end-to-end support to secure your project’s success.
Companies that trust us
How we ensure you get the best ROI from AI
efficiently and accurately harness AI at scale.
Discovery and Feasibility
We provide you with a Proof of Concept (PoC) to de-risk your investment and ensure the success of your AI initiatives.
- Mitigate risks with thorough planning, strategy, and informed assessments
- Retain IP ownership for all solutions developed on your behalf
- Avoid over-investment by validating feasibility before full commitment
- Receive expert opinions on the optimal solution for you problem
Data Acquisition
Medical Data
AgTech Data
AI Speech Data
AI Localization Data
Sensor Data
Statistical Data
Tabular Data
Synthetic Data
Data Annotation
- Aya combines advanced tech and human expertise for image and video labeling tasks like bounding boxes, segmentation, polygons, and key point annotation
- Aya’s C1/C2 level linguists specialize in NLP tasks, including Named Entity Recognition, Sentiment Analysis, transcription, translation, and localization in multiple languages
- Aya has experts in 3D point cloud data labeling from LiDAR sensors, using 3D Bounding Box, 3D Polygon, and 3D Semantic Segmentation
- Aya is adept at handling diverse labeling needs with precision and expertise across various languages and data types
Model Training and Development
At Aya Data, we specialise in developing customised AI solutions to unlock your business potential. Our team of experts crafts a wide range of models, from traditional machine learning algorithms to state-of-the-art deep learning architectures. We work across the AI spectrum, tackling projects that range from logistic regression and gradient boosting to advanced BERT models for NLP and convolutional neural networks (CNNs) for computer vision. Our comprehensive approach encompasses expert guidance on model selection, efficient data preprocessing, and meticulous training and fine-tuning. With a proven track record of driving transformative results, we’re committed to pushing the boundaries of AI innovation.
Computer Vision
We build models ranging from classic CNNs to advanced architectures like YOLO and Mask R-CNN, enabling real-time object detection, image classification, and complex video understanding. If you’re short on data, we can generate detailed synthetic data to fit your application.
Natural Language Processing
Our advanced NLP consulting services support the creation of AI applications that truly comprehend complex language, delivering impactful results. With techniques like retrieval augmented generation (RAG), we can supercharge your models with external knowledge bases, boosting their contextual and analytical abilities.
Generative AI
Our expert team will work with you to build and train models like GANs, VAEs, diffusion networks, and more. Our model development and deployment processes also incorporate reinforcement learning with human feedback (RLHF) techniques to continuously improve model performance based on user feedback.
Data Services
We know that great AI starts with great data. That’s why we offer comprehensive data services to help you build the strong foundation your models need. We’ll work with you to assess your current data landscape, identify gaps and opportunities, and develop a custom data strategy aligned with your business problem.
Model Deployment
Deploying AI models into production environments is critical in realising their potential in real-world settings. At Aya Data, we're committed to helping you get your models out of the lab and into the real world, where they can start driving results. We use state-of-the-art deployment technologies, such as containerisation and cloud platforms, to ensure your AI solutions are reliable, efficient, and easily maintainable. Our model development and deployment processes can incorporate reinforcement learning with human feedback (RLHF) techniques to continuously improve model performance over time. We can integrate models with your existing tech stack or deploy them in custom software, providing flexibility to suit your specific needs.
Ongoing Maintenance & Upgrades
Even after deployment, our commitment to your AI solution’s success continues. We ensure your models remain cutting-edge and aligned with your business goals through rigorous testing, proactive monitoring, and continuous refinement.
- Test models to ensure they meet commercial objectives
- Safeguard against changing context and model drift w/ human-in-the-loop oversight
- Continuously update AI solutions with new technology, data, and feedback
- Provide regular performance reviews and optimization to sustain model efficacy
Why Use Aya for Your AI Consulting Project
Exceptional Customer EXPERIENCE
- 1.Tight communication loop for project alignment
- 2.Transparent pricing for cost clarity
- 3.Dedicated domain-specific project management teams
- 4.Guiding AI initiatives from conception
- 5.Ensuring transparency throughout project lifecycle
Unwavering QUALITY
- 1.Custom quality control for projects
- 2.High-performance AI meeting specific needs
- 3.Ethically-driven annotation workflows
- 4 Strict ISO 9001, GDPR, SOC2 compliance
- 5.Tailored solutions for niche AI challenges
Unparalleled EXPERTISE
- 1.Large team of dedicated domainspecific data specialists
- 2. Expertise across industries andapplications
- 3. Experienced data scientists andengineers
- 4. Cutting-edge technical knowledge for projects
- 5. Broad network of expert resources
What Our Clients
Say About Us
Case Studies
Real-Time Transcription of American Police Radios
Aya Data partnered with a US technology firm to provide real-time transcription of American police radio communications. Our team of C1/C2 English speakers transcribed over 500,000 police calls in 18 months, overcoming poor audio quality and colloquial language challenges. We consistently outperformed all other vendors in accuracy, contributing directly to the successful launch of the client's crime alert app.
Using AI and Drones to Create Precision Agricultural Systems for Commercial Farming
Aya Data partnered with a 6,000-ha palm plantation in Ghana to develop a computer vision-powered crop management system.
Our team labelled aerial RGB image datasets, which were used to train a highly accurate palm-counting model. The solution, deployed through an ArcGIS dashboard, enabled the client to visualise plant count and other parameters, vastly enhancing their farming operations.
AI Consulting Blog Post
Sustainable Dev’t In Ghana
The latest survey by the Ghana Statistical Service revealed that 42,396 agribusiness firms closed during the lockdown, with 16,091 of those firms still remaining closed. The impact of COVID-19 was more pronounced in the service and industry sectors, particularly for agribusiness firms that closed as a result of the lockdown. Furthermore, 55.2 percent of the total workforce in agribusiness were laid off due to the pandemic.
Objectivity and Ground Truth in AI
Ground truth’ is somewhat of a confusing machine learning buzzword. Discussions of the ground truth naturally touch on areas such as bias, representation, and objectivity, and it’s a concept worthy of discussion. One of the main pitfalls of AI is that it’s often assumed to be inherently objective. The cold, objective rationalism of AI manifests in sci-fi characters and robots like Walter and David in Alien or even the machines in the Matrix.
Predicting Crime With AI: Navigating Ethical Issues
In June 2022, a cross-discipline team of researchers at the University of Chicago created an AI model that could predict the location and rate of crime in the city with 90% accuracy. The team utilized citywide crime open data between the years of 2014 and 2016, dividing the city into squares of around 1000ft (300m). The resulting model could predict the square where crime was most likely to occur 1-week in advance.
AI Embodies The Bias Of Internet Content
OpenAI is a significant player in the modern artificial intelligence (AI) and machine learning (ML) space. While the parent company is a non-profit, it also consists of a for-profit company that received a $1 billion investment from Microsoft in 2019. OpenAI has become well-known for its novel and innovative AIs, including Jukebox, a neural net that generates music, DALL-E that generates images from text, and GPT-3, which produces human-like text.
What is a Human-in-the-Loop?
Machine learning (ML) and artificial intelligence (AI) models still largely require the input of humans to train, tune and test models to ensure their accuracy and performance. When humans are positioned in the ML and AI loop or cycle, they can be referred to as humans-in-the-loop (HITLs). HITL means leveraging both human and machine decision-making to train, optimize and test machine learning models.
Top 10 Books on Machine Learning and AI
Machine learning (ML) and artificial intelligence (AI) are foundational technologies in today’s technologically evolved and hyper-digital era. Computers changed the world, but ML and AI are changing computers by equipping them with the ability to process complex information at unprecedented scale and speed. Intellligent, human-like AIs are becoming more common, and we’re not even close to the peak yet.
The Impacts of Bad AI
AI is a force of good, right? That’s what the industry must strive for, but the positive impacts of AI are far from guaranteed. AI is the hallmark technology of our era, but it’s entangled in risks, and even die-hard futurists have niggling worries that advanced AI may signal our demise. You only have to look at how we’ve imagined AI in popular culture, film, and literature to understand that AI inspires fear as well as awe.
What is a Human-in-the-Loop?
In 2021, the European Commission published its proposal for Artificial Intelligence Regulation, or in their words; “a proposal for a Regulation laying down harmonized rules on artificial intelligence.” This is expected to be the first coherent piece of ongoing regulation and legislation on AI. Not only will the regulation change the way future AI projects are developed in the EU and across much of the world, but it’ll also change the way current AI projects are deployed and distributed.