Computer vision is rapidly transitioning from niche research interest to transformative business capability. By automatically extracting insights from visual data, CV enables game-changing applications like facial recognition, defect detection, and autonomous vehicles. As a result, companies across sectors are ramping up investments in this space.
But while the potential impact of CV is far-reaching, effectively deploying these technologies poses challenges that can easily derail projects or constrain value. This is driving growing demand for external consulting help.
This comprehensive guide explores the key benefits of seeking expert CV consulting along with best practices for selecting the right partner to meet your needs. With insights drawn from my decade of experience in data extraction and analytics, I‘ll provide an in-depth look at:
- The expanding real-world CV landscape
- Common pitfalls faced when adopting CV
- How experienced consultants can accelerate success
- Criteria for evaluating and choosing a consulting firm
- Strategies to gain internal buy-in and ensure ROI
Let‘s start by examining the rapid growth trajectory of computer vision and what‘s fueling rising adoption.
The Expanding Computer Vision Landscape
Computer vision leverages AI techniques like deep learning neural networks to extract high-value information from digital images, videos and other visual inputs. This enables transformative capabilities like:
- Image classification – Identifying objects in images
- Object detection – Locating objects within images or videos
- Facial recognition – Detecting, verifying and analyzing faces
- OCR – Converting text in images and documents into machine-readable data
- Anomaly detection – Identifying defects or irregularities in visual inspections
- Image segmentation – Partitioning images into distinct regions or categories
As these technologies improve and mature, we‘re seeing surging investment and real-world deployment across sectors:
- Industrial manufacturing – CV for product defect detection, predictive maintenance, inventory management
- Automotive – Self-driving vehicles, driver safety monitoring, intelligent traffic management
- Healthcare – Medical image analysis for improved diagnosis, robotic surgical assistance
- Retail – Cashierless stores, personalized marketing, analytics to optimize operations
- Security – Access control, enhanced surveillance and monitoring, crowd analytics
In fact, Tractica forecasts that the global computer vision market will swell to $48.6 billion by 2022, a cumulative annual growth rate of 7.3%. Key drivers include:
- Expanding datasets from proliferation of cameras, sensors and imaging devices
- Growth of edge computing improving real-time video analysis
- Advances in deep learning algorithms, GPUs and neural networks
- Increased investment in autonomous vehicles, robotics, drones
- Migration to cloud infrastructure providing scalable processing power
Clearly computer vision adoption is accelerating across industries given the immense new value it unlocks. However, companies seeking to leverage CV face an array of challenges that can impede success.
Challenges With Computer Vision Adoption
While computer vision offers game-changing capabilities, it presents multifaceted technical and organizational hurdles that can easily derail projects if not addressed:
Insufficient Internal Expertise
CV solutions require specialized skills like:
- Expertise in relevant techniques – image classification, object detection, OCR, etc.
- Proficiency in ML/DL tools – OpenCV, TensorFlow, Caffe, Keras, etc.
- Data engineering skills – collection, labeling, augmentation, analysis
- Infrastructure architecture – sensors, cameras, cloud, edge devices
- Production deployment experience – DevOps, MLOps, CI/CD automation
Most companies struggle to staff or train teams with this full spectrum of required capabilities. Critical gaps can jeopardize projects.
Prohibitive Data Requirements
CV models rely on huge training datasets to learn effectively. For example, Waymo‘s autonomous driving AI ingests over 25,000 driving segments daily. But amassing this data presents obstacles:
- Privacy – Collecting sufficient personal visual data raises regulatory issues
- Costs – Acquiring comprehensive, diverse, labeled datasets is enormously expensive
- Time – Manually labeling thousands of data samples is cumbersome and slow
As a result, many CV initiatives flounder due to inadequate training data.
Hardware and Infrastructure Demands
Computer vision applications require specialized hardware like high-resolution cameras, sensors and computing devices. Architecting and maintaining this infrastructure in-house can become complex and costly.
Even leveraging cloud platforms poses challenges in configuring optimized, scalable environments. Lacking robust infrastructure prevents delivering production-grade CV solutions.
Integration With Legacy Systems
To generate business impact, new CV models must integrate with existing enterprise systems from ERP and CRM to proprietary software. This requires expertise that most companies lack.
Flawed integrations that are brittle or fail to connect data flows effectively negate potential value. Smooth integration is essential but rarely simple.
Organizational Resistance
Since CV represents disruptive change, inertia and skepticism are common. Stakeholders may resist diverting resources from current initiatives they better understand.
Without executive commitment and a clear business case tied to strategic goals, adoption stalls. Savvy change management is key to driving culture change.
Given these multifaceted complexities, many companies are now seeking outside specialists to de-risk CV adoption.
The Upside of Computer Vision Consulting
Computer vision consultants offer expertise and experience that can mitigate project risks and accelerate value realization. Key advantages include:
Faster Deployments
By leveraging consultants‘ specialized knowledge and reusable assets, companies can expedite CV solution delivery and avoid common missteps. Experienced partners have worked on similar projects enabling them to:
- Quickly architect optimized infrastructure solutions
- Recommend proven algorithms and models tailored to the use case
- Rapidly label and process datasets based on templates
- Streamline integration using patterns and connectors from past projects
This prevents wasted time and rework associated with internal trial-and-error development. According to recent research from Deloitte, working with consultants reduced deployment time by 62% for AI initiatives.
Reduced Risk
Consultants also bring experience managing the risks associated with CV adoption from privacy concerns to model degradation. Partners can provide guidance to:
- Leverage data labeling and augmentation techniques to optimize small datasets
- Implement MLOps to monitor models and continually enhance accuracy
- Architect infrastructure for optimal scalability, throughput and cost
- Incorporate responsible AI practices that address biases and ethical risks
This expertise lowers project uncertainty and delivers solutions with greater predictability.
Enhanced Data Leverage
Skilled CV consultants understand how to extract maximum value from client data. Capabilities like:
- Mining public datasets relevant to the use case
- Securely labeling sensitive new data
- Augmenting data to increase model robustness
- Anonymizing data to maintain privacy
These data skills amplify available datasets to improve model training. Augmenting internal data practices drives better CV outcomes.
Increased Business Alignment
Experienced consultants also excel at linking CV initiatives to business priorities and outcomes. This includes steps like:
- Building executive-friendly business cases grounded in strategic goals
- Quantifying expected costs, risks and ROI to secure buy-in
- Structuring solutions and metrics to optimize targeted business objectives
- Managing change and training to drive user adoption
This alignment helps smooth deployment while delivering maximum business impact.
Ongoing Performance Optimization
Even after initial launch, CV solutions require continuous enhancement and adaptation. Consultants provide an ongoing partnership through areas like:
- Monitoring models and initiating refresh cycles
- Re-training models as new data is collected over time
- Tuning algorithms and parameters to improve accuracy
- Identifying performance drifts and troubleshooting root causes
This expert optimization ensures your CV deployment continues driving value over time.
According to a recent McKinsey survey of AI adopters, 24% of respondents reported their initiatives failed to generate projected financial returns. Tapping external consultants mitigates this risk and improves outcomes.
Next let‘s explore best practices for evaluating and selecting the right CV consulting partner.
How to Select a Computer Vision Consultant
Once the advantages of external consulting help are clear, prudent vetting and selection is critical for identifying the best match for your initiative and environment. Key considerations include:
Relevant Industry and Application Expertise
Look for proven experience developing solutions in your vertical and specialty. For instance, manufacturing automation expertise differs from building medical diagnostic tools.
Ideally the consultant has successfully delivered similar solutions leveraging techniques like image classification, object detection, OCR and segmentation tailored to your goals. This direct project experience increases chances of success.
Technical Capabilities and Resources
Take stock of the consultant‘s technical breadth and depth across areas like:
- CV algorithms – object detection, image segmentation, OCR, etc.
- Development tools – OpenCV, TensorFlow, Caffe, Keras, etc.
- Infrastructure – cloud, edge devices, cameras, sensors, GPUs
- Data engineering – labeling, augmentation, analysis, privacy
- Production deployment – CI/CD, MLOps, DevOps
End-to-end capabilities through advanced algorithms, robust data practices, specialized hardware, and smooth deployment orchestration are positive signals.
Also assess the size of the consultant‘s technical team and their backgrounds. Larger firms with specialized practitioners are better positioned to scale.
Client References and Project Portfolio
The best indicator of aptitude is proven success on prior engagements. Review project examples similar to yours and speak to provided client references.
Look for case studies that include performance benchmarks, business impact metrics and direct client quotes. This validates hands-on ability to deliver tangible CV value.
Staffing and Pricing Models
Explore how the consultant structures engagements to understand service flexibility:
- Staff augmentation – Add specialized CV experts to temporarily expand teams
- Project-based – Fixed scope and pricing to address a defined business need
- Retainer – Ongoing partnership for sustained solution optimization
Also examine pricing models like time and materials, fixed bid, or risk-sharing approaches to align costs to your budgeting needs.
Compliance Expertise
For sensitive applications, assess capabilities around data privacy, anonymization, and regulations like GDPR and HIPAA. Look for demonstrated experience building compliant CV solutions that mitigate risk.
Communication and Collaboration
Since success hinges on working together, evaluate the consultant‘s commitment to transparency, knowledge sharing, and culture alignment.
Explore both project governance and technical protocols they use to enable collaboration. Confirm flexible delivery models that meet your needs.
Overcoming Internal Adoption Roadblocks
While the benefits of strategic CV consulting help are compelling, some companies still encounter internal resistance to engaging external partners stemming from:
- Not invented here syndrome – Engineers clinging to preferences for developing solutions internally rather than leveraging outside IP and expertise
- Budget constraints – Leadership hesitant to fund new consulting partnerships amid other spending priorities
- Security concerns – Anxiety sharing sensitive data assets with external vendors
- Compliance risks – Perceived regulatory and ethical issues associating with third-party data usage
- Lack of vertical expertise – Skepticism that generalist consultants can deliver specialized solutions
Navigating these roadblocks requires strategic messaging and change management:
- Communicate accelerated value – Demonstrate how consultants expedite solution delivery and ROI compared to internal development
- Quantify opportunity costs – Profile revenue loss and competitive threats from CV delays to build urgency for external help
- Highlight security competency – Research partners’ information security and privacy certifications and practices
- Socialize success stories – Reference clients in similar industries who achieved CV breakthroughs with consulting partners
- Rightsize partnerships – Start with smaller pilot engagements focused on pain points to demonstrate incremental value delivery with minimal risk
With compelling messaging reinforced by pilot successes, companies can overcome inertia to embrace strategic consultants accelerating their CV advantage.
Realizing the Full Potential of Computer Vision
As computer vision adoption accelerates, it is ushering in paradigm-shifting applications that will redefine industries in the years ahead. However, despite the vast possibilities, effectively harnessing CV presents very real technical and organizational challenges that impede results for many companies.
The good news is that external consultants stand ready to help mitigate these hurdles through specialized expertise. By combining internal strengths with the expansive experience and resources of a seasoned CV consulting partner, companies can overcome obstacles to achieve more rapid and robust solution delivery.
The keys lie in confirming targeted domain experience, evaluating end-to-end technical capabilities, validating client success, and ensuring delivery models align to your needs. With prudent vetting and selection, strategic consultants become force multipliers enabling transformative computer vision impact and business value.
To further explore advanced computer vision consulting partners tailored to your industry, technology needs and use cases visit AIMultiple‘s curated directory of top CV consulting firms. Their matching platform helps you identify partners that best align to your specific environment and initiatives to drive success.