Watchmaker Genomics, a company specializing in protein engineering and enzyme manufacturing, faced a significant challenge in establishing a robust quality control system. The company's products are used in CAP/CLIA laboratories for sample analysis, making airtight product quality crucial. CEO Trey Foskett, having established several other companies in the past, was aware of the business impact of implementing a digital quality approach early on, rather than adding it to pre-existing processes. The company was eager to establish a single, central mechanism for managing quality, from accessing daily information and documenting work to accessing rich quality data and being able to quickly and nimbly respond to defects with controlled CAPA plans. Quality Control Manager Skyler Mishkin was tasked with finding the best possible electronic quality management system (eQMS), and the search began within the first few months of the company's establishment.

Bracknell Forest Council (BFC) serves a rapidly growing population of over 125,000. The council's digital team is tasked with delivering efficient and accessible services to all citizens, including its out-of-hours handling service, the Berkshire Emergency Duty Service (EDS). The EDS team, which serves almost a million residents, responds to crisis welfare and safety situations outside regular office hours. To support this team, BFC needed a comprehensive solution that could handle multiple case types with specific workflows, maintain data security, and replace manual processes to reduce errors and improve reporting. The solution also needed to offer more automated self-service to free the team from routine administrative tasks. The EDS team deals with time-consuming, emotional, and complex cases, including supporting the homeless, children who need protection, and those having a mental health crisis. Each situation requires careful assessment, recommendation of a solution, and/or a referral.

Imperial College Healthcare NHS Trust, one of the UK's largest trusts, was facing a significant challenge in managing patient contacts across their Central Booking Outpatients, Admissions and Switchboard teams. The trust provides acute and specialist healthcare to approximately 1.5 million people every year across five busy sites in north-west London. The Switchboard alone used to handle an average of 11,500 interactions a day. However, call fluctuations and siloed departments made it difficult to meet daily demand, leaving upwards of 800 calls unanswered at times. These missed calls not only represented a lost opportunity to free up availability of limited clinical resources but also resulted in a significant amount of failure demand. The trust needed a contact centre solution that would allow them to manage their patient contacts more effectively, delivering an omnichannel digital service without the need for extra headcount.

Imperial College Healthcare NHS Trust, one of the UK’s largest trusts, provides acute and specialist healthcare to around 1.5 million people every year across five busy sites in north-west London. The trust was struggling with handling over 11,500 inbound calls a day, with agents having little time to determine the purpose of the call before routing it. They had a target KPI of answering 70% of all calls within 30 seconds. The challenge was to optimize inbound and emergency calls by tackling incorrect transfers and relieving strain on operators. This was necessary to reduce caller frustration, ward disruptions, and rising call volumes. In the case of emergency calls, where the time to answer is under 10 seconds, the trust needed to rapidly identify these priority calls amid high call volumes to trigger emergency protocols.

The healthcare sector is often burdened with administrative tasks that can limit the capacity of staff and resources. Traditional methods of patient engagement, such as appointment notifications and waiting list validations, can be time-consuming and inefficient. Additionally, the reliance on physical mail for appointment letters can lead to delays and lost information. The challenge was to find a solution that could reduce the administrative burden on staff, increase capacity, and improve patient engagement, while also integrating seamlessly with existing healthcare systems.

Network Certification Body (NCB), a leading provider of railway assurance and certification on infrastructure, vehicle, and freight projects in the UK and worldwide, was facing a challenge with its existing IT systems. With an average of 200 rail projects being delivered at any one time, safety was its first priority. However, the existing systems for managing assessment service delivery were inefficient. NCB needed to replace largely manual information management with automated document generation, while supporting the NCB’s Progressive Assurance Methodology. The new solution would need to administer complex document templates and facilitate efficient and effective client communications between NCB and its clients.

Newcastle City Council (NCC), the local government authority for the city and metropolitan borough of Newcastle upon Tyne, faced a significant challenge in making community grants more accessible to its citizens. The council needed a digital-first case management solution that could integrate multiple technologies, automate processes, and deliver accurate reporting for compliance. The ultimate goal was to provide a streamlined and transparent end-to-end application process for a range of grants, including the Clear Air Zone (CAZ) grant. The council team was burdened with handling numerous unstructured emails and telephone calls, leading to manual re-keying of customer data and reliance on spreadsheets for payment processing. With limited validation capability, the risk of claim fraud, error, and audit failure was high. Additionally, NCC was legally required to reduce traffic-related pollution levels, necessitating a simple way for owners of specific vehicles to check eligibility and apply for grants.

The Royal Cornwall Hospitals NHS Trust (RCHT) is the primary provider of acute and specialist care services in Cornwall and the Isles of Scilly, serving a population of around 470,000 people. This number significantly increases during peak visitor times. RCHT embarked on an outpatient transformation program to optimize their referrals and provide patients with more control and convenience over their appointments. The goal was to reduce the time patients spent traveling to hospital appointments and waiting rooms and improve access to follow-up hospital care. However, the challenge was that there were numerous different referral pathways into their organization, making it difficult to streamline and optimize the process.

Valleys to Coast (V2C), a housing provider managing over 6,000 homes across South Wales, was facing significant challenges with its legacy systems. The lack of interoperability between two housing management systems resulted in poor visibility of cases, leading to data duplication and inadequate reporting. The organization was in dire need of a unified case management solution that could be easily adapted by in-house staff to meet the evolving needs of tenants. The customer service staff was under immense stress due to the need to constantly follow up with internal teams and manage tenant experiences. The lack of visibility into case progress led to inefficiencies as multiple advisors often ended up working on the same case simultaneously. The shift to remote work further exacerbated these issues.

Worcestershire County Council (WCC) serves over half a million people across an area of 672 square miles. The council had previously consolidated its services and implemented a new Netcall contact centre platform. However, they were keen to further exploit the potential of the integrated chatbot technology. The council aimed to provide a 24/7 service to citizens, reduce inbound call transfers to customer service teams, refine processes to support customer enquiries efficiently, proactively provide information and guidance, and manage peak communication volumes. The council's journey to enhance efficiency and customer experience had progressed from voice channel to web chat and then to chatbots. However, agents were still required to handle queries that could be resolved through chatbots. The council was focused on refining chatbot processes to make them more effective for citizens.

Yource, a leader in customer contact and business process outsourcing, was on a path of complete digital transformation. The company was looking for a development platform that could provide a secure environment and enable faster development time to build applications for its internal processes. As a technology-first company, Yource had been a low-code user and a WaveMaker client since 2019, successfully implementing critical internal applications with low-code. However, the company needed a solution that offered flexibility in terms of customizing code, and the ability to deliver simple to complex applications quickly. This was crucial to give developers sufficient freedom and space within the tool to get the best of both worlds.

Adevinta, a global online classifieds specialist, operates over 25 platforms across 11 countries, reaching hundreds of millions of users monthly. Their mission is to provide the best user experience for buying and selling goods and services online. To achieve this, they needed a centralized analytics and dashboarding tool to monitor their seller's advertisements, track interactions, and improve performance in real-time. The Central Data Products team at Adevinta was tasked with building data and machine learning products to support their various marketplaces. They faced a complex challenge of needing a solution that could scale, provide end-user facing analytics capabilities with low latency and high throughput, and consider aspects such as reusability, uptime, and scalability. Adevinta required a user-facing real-time analytics and dashboarding solution that would allow the sellers to monitor their advertisements in real-time, tracking views, favorites, and likes, and capturing every interaction that occurs on their marketplaces.

AdGreetz, a leading AdTech and MarTech personalization platform, specializes in creating and distributing millions of intelligent, data-driven, hyper-personalized ads and messages across 26 diverse channels. The company processes millions of ad impressions daily, which necessitates a high-performance, cost-effective solution for their data storage and analytics needs. Initially, AdGreetz used AWS Athena for their data processing needs, but it failed to meet their increasing performance and data demands. They then turned to Snowflake, but the cost proved to be prohibitive for their data volume and query performance. The company needed a solution that could handle their vast data volume, provide quick query times, and fit within their budget.

Admixer, an Ad-Tech company, was facing a significant challenge in managing the increasing load on their advertising exchange platform. Initially, the platform was based on the sale of local inventory by external DSPs, but as it began to aggregate the traffic of external SSPs, the load on their processing and storage increased significantly. By the end of 2016, the share of external inventory had risen from 3% to over 90%, translating to an increase from 100 million to 3 billion requests. The existing relational databases could not handle the massive influx of inserts for statistics records. Furthermore, the company was using Azure Table Storage for storing and issuing statistics, but as the number of transactions and the amount of data increased, this solution became suboptimal due to the charges for the number of transactions and the amount of data. Admixer needed a solution that could display real-time advertising transaction statistics, handle a significant amount of data for insertion, aggregate received data, scale the data warehouse as requests grew, and provide full control over costs.

BENOCS, a company that provides network traffic optimization and monitoring for some of the world's largest telecommunications providers, faced the challenge of monitoring and analyzing massive amounts of data traffic. The data was not static but constantly moving through cyberspace, requiring the company to factor in time as an additional dimension. BENOCS Flow Analytics users needed to investigate incidents that occurred in specific time frames, necessitating fast access to specific time ranges while ignoring irrelevant data. The company also had to deal with the challenge of analyzing network traffic at high complexity and speeds, especially in diverse environments with asynchronous data feeds. Across different network setups, BENOCS had to unify the data sources and correlate the incoming network information.

Coinpaprika, a leading cryptocurrency market data platform, was facing challenges with their existing data management system. They were using InfluxDB for their time-series data and MySQL for transactional data. However, as their data volume grew, they encountered several issues with InfluxDB. The team found it difficult to extract useful metrics from the system, and extending the timeframe for queries often led to server overload. They also experienced problems with response times due to merging data blocks. The open-source version of InfluxDB lacked built-in replication and scalability, which were critical for Coinpaprika's infrastructure. Coinpaprika needed a solution that could handle their increasing data volume, provide useful metrics, and offer improved performance and scalability.

Contentsquare, a SaaS company, was facing significant challenges with its existing Elasticsearch setup. The company had 14 Elasticsearch clusters in production, each with 30 nodes. However, they were struggling with horizontal scalability, as they were unable to assemble larger clusters and maintain their stability for their workload. This limitation in cluster size meant that they could not handle any tenant that would not fit into a single cluster, severely restricting their ability to grow. The upper bound on the amount of traffic they could handle was slowing down the company's growth for technical reasons, which was unacceptable. They were left with two options: either find a way to host each tenant efficiently in a multi-cluster setup or migrate to a more scalable technology.

Software applications generate terabytes of data that can be used to make informed decisions. However, transforming this data into visual insights for users can be a challenge. The task of delivering analytics in SaaS is two-fold: providing an easy-to-use, interactive, and personalized experience for end-users, and building a coherent and high-performing data architecture with tailored visualizations quickly and painlessly. The more advanced the analytics, the harder it becomes for developers to maintain. Additionally, there is the complexity of data security, ensuring that each user only has access to their personal data. The challenge lies in scaling tailored insights to hundreds or even thousands of users.

Darwinium, a digital risk platform, was facing several challenges in the security and fraud domain. The platform needed to ingest and process data at a high throughput, deal with large volumes of data, and have capabilities to analyze data in a complex way. The database backend needed to handle high-speed writes and serve data for analysis as soon as it was ingested. Darwinium's real-time engine continuously profiles and monitors a digital asset, resulting in large volumes of data. The database needed to be capable of analyzing data at scale, and potentially process an entire year's worth of data. Technical types of fraud and security challenges required storing most digital datapoints for future investigations. The nature of analyzing fraudulent data required complex interactive analysis, and a database system that could respond in timeframes of 1 second or less, while providing a feature-rich functional toolbox.

Modern enterprises are investing heavily in security products due to the increasing cyber risks and their impact on businesses. A typical large enterprise today uses more than a dozen security technologies, which emit data in various shapes and sizes, making it difficult to make sense of the data. Security Information and Event Management (SIEM) systems, designed for immutable time series event data, struggle with the mutable nature of security data. For instance, the state of an alert could change from 'open' to 'closed', and SIEMs cannot update this change. The solution is to re-insert the updated data and query the most recent data, which is challenging on append-only systems like SIEMs. Additionally, SIEM companies have stopped innovating and investing in solving basic problems such as data normalization. Dassana, a security data lake, aims to address these challenges.

DeepL, a language translation service, was looking to enhance its analytics capabilities in a privacy-friendly manner in 2020. The company wanted to self-host a solution that could handle large amounts of data and provide quick query times. They evaluated several options, including the Hadoop world, but found it too maintenance-intensive and time-consuming to set up. DeepL also wanted to automate the process of changing table schemas when frontend developers created new events, which would have otherwise overwhelmed the team. The company needed a system that could handle complex events and queries to understand user interactions, something that traditional tools like Google Analytics couldn't provide. Additionally, DeepL wanted to maintain full control over the data while keeping user privacy in mind.

The challenge at hand was to provide a seamless and efficient platform for teams to discover and share insights from their data. The existing systems lacked a central place for collaboration and efficient work on data science projects. Moreover, the transitions between Python and SQL were not smooth, requiring a Python connector. There was also a need for a SQL editor with features like formatting, autocomplete, and linting right in the notebook.

hireEZ, an AI-powered recruitment software company, was facing a significant challenge in their go-to-market strategy. The team was making decisions based on what Senior Growth Manager, Vu Thai, referred to as 'fuzzy data.' The company was investing heavily in ad campaigns and sponsored events, but lacked the necessary tracking to understand how these campaigns resonated with potential buyers. While they were not losing money on paid ads, the return on investment was low. Furthermore, there was a lack of alignment between the marketing and sales teams. hireEZ needed a solution that would provide actionable insights to target their ideal customer profiles (ICPs), clarify customer profile data, and align their marketing and sales teams.

Marathon Health, a nationwide network healthcare solution, was facing significant challenges with their marketing and sales processes. Their go-to-market team was overworked and understaffed, leading to numerous unaddressed inbound requests, ignored accounts, and gaps in their marketing-to-sales qualification process. Their tech stack was outdated and provided limited insights, which resulted in a lack of demand-generation capabilities. The marketing team was primarily focused on creative tasks, while the sales team relied on purchased contact lists and cold calls, often reaching out to customers with no intent to purchase. This inefficient approach resulted in a lengthy and wasteful sales cycle. Furthermore, their tech stack provided a limited view of first-party data, failing to deliver crucial insights needed to reach companies actively seeking a solution. This deficiency in the middle of the funnel meant Marathon Health lacked the resources to contact and nurture thousands of leads.

Martal Group, a leading lead-generation and sales solution provider, faced a significant challenge during the COVID-19 pandemic. The pandemic altered the landscape of cold outreach, necessitating a shift in Martal Group's sales strategy. The company recognized the need to adopt an account-based marketing (ABM) approach, which involved engaging smaller groups within a single account with more targeted messaging. However, traditional ABM programs often require substantial time and effort to scale, which contradicted Martal Group's commitment to efficiency in terms of time, budget, and tools. As on-demand sales representatives, the tools they use directly impact the results they produce for their clients. Therefore, Martal Group needed an ABM solution that could deliver robust data and revenue without sacrificing time, money, or resources.

NanaWall Systems, a leading manufacturer of opening glass wall systems, has been using Account-Based Marketing (ABM) strategies for years, even before the term 'ABM' became popular. The company used predictive analytics tools to score opportunities and maintain its industry-leading position. However, as ABM and predictive analytics technologies continued to evolve, NanaWall sought to enhance its competitive edge. The manufacturing industry isn't a significant user of martech, which had been a competitive differentiator for NanaWall. The challenge was to maintain this edge in the face of improving technologies. NanaWall was intrigued by 6sense's ability to combine account fit and engagement scoring, as opposed to other solutions that focused solely on account fit.

OneSourceVirtual (OSV), a global leader in payroll, finance, and HR services, was seeking an end-to-end account engagement platform to enhance their campaign strategies and provide a seamless, personalized customer experience. They aimed to reach out to accounts in-market for their solutions, targeting the right buyer personas through the right channels at the right stage in their buyer journey. However, without the proper technology, executing this full account engagement approach was challenging and nearly impossible to scale and sustain. They needed a solution that could support building complex audience segments for their various targeted campaigns, offer deep granularity in monitoring campaign success, and provide predictive analytics for hyper-personalized sales and marketing efforts.

PTC was in search of a solution that could combine account-intent programs with AI platforms. The goal was to deliver a customer-centric digital experience that provides value-led content at every buyer interaction, leading to pipeline growth. The company has a strong marketing ops team with a 'data-driven everything' mentality. When it came to integrating new solutions into its existing tech stack, PTC invested significant diligence into its research. After thorough evaluations over several months, PTC decided to simultaneously sign contracts with 6sense, Drift, and People.ai.

Qualtrics, a leading experience management platform, has experienced exponential growth over the past two decades. With 5,000 employees and 16,000 customers, the company has become a go-to solution for enhancing customer, employee, product, and brand experiences. However, with this growth came challenges. To continue expanding their customer base with high-impact accounts, Qualtrics needed to use targeted and reproducible approaches. The company was looking for ways to eliminate guesswork and confidently engage the right accounts at the right time. In 2019, they turned to 6sense to scale up. The challenge was to optimize their LinkedIn advertising strategy, suppress weak accounts, and incubate stronger ones.

Qualtrics, a company synonymous with experience management, faced a challenge in optimizing their website for all visitors, particularly target accounts. Despite having traditional channels set up for users to interact with their brand, such as filling out a form on their website or talking to sales via phone or email, they lacked a digital aspect. The team wanted to ensure that no matter the channel, a user could easily get in touch with their sales team. They also aimed to build an incremental pipeline through the website and generate net-new names from website visitors. Simultaneously, they were rolling out a comprehensive account-based marketing (ABM) strategy, aiming to enhance their existing good practices.