The Leader in API Analytics
Analyzing API usage patterns to build APIs developers love.
Rev.ai is an automated speech recognition offering by Rev.com for developers that can make audio and video content searchable and accessible. They built rev.ai from millions of hours of human-transcribed content from Rev.com's om-demand audio transaction services. Rev has two primary APIs. One is for rev.ai's speech to text API, which performs automated speech recognition on input audio / video. The other is Rev.com's transcription and caption API, which allows integration with their human transcription and captioning service trusted by over 100,000 customers including Visa, Salesforce, and Disney. In addition to exposing these APIs to customers, Rev also uses these APIs internally for their mobile apps including Rev Voice Recorder and Call Recorder.
As VP of Engineering for rev.ai, Dan Kokotov oversees the team that develops these APIs. He needed a solution to be able to monitor and analyze that API traffic. They already had internal logging of API calls to Kibana, an on-premises general-purpose logging tool. However, they couldn't get the advanced filtering and high-level analytics they were looking for from logs alone. They were also looking for a solution to aid customer success in debugging specific customer issues and something to get automatic warnings when unusual patterns happen on the API. They looked at a variety of solutions including API proxies/gateways. Their main alternative was just sticking with their internal logger.
"There were really no other services we found that offer this kind of feature set, except for much more heavyweight API proxy / management services like Apigee."Dan Kokotov, VP of Engineering for rev.ai
He didn't want to go the API gateway route, as they don't really need any of the other features those services provide. Rev built a custom data collection integration on top of our C# API lib which does not sit in the path of API calls and only captures data passively (since then, Moesif released a higher level .NET SDK on top of the C# API Lib to make integration even easier). The Rev team has been successfully using Moesif for deeper analytics that logging doesn't provide. They especially use Moesif when wanting to do a bit more digging to see if an issue exhibits certain patterns, and to proactively to explore API usage patterns understanding how their customers use their API such as time of day, geo location, etc. Moesif has reduced the time to debug new customer issues that pop up.
Measuring adoption of integration partners
Tallyfy provides workflow software that enables anyone to define and track processes. Companies like Oracle, Nestle, and Emerson depend on their API and countless API-powered integrations to other SaaS companies which also have API's. With his technical background, Amit Kothari, Tallyfy's CEO, likes to get deeply involved in architectural decisions for their platform. Tallyfy was looking for a solution to capture API requests at the edge with a very low-latency architecture for their staging and production APIs.Read Case Study
Thanks for creating Moesif. I'm a plugin developer for DHL Parcel. Me and my team are creating plugins for popular eCommerce web shops that communicates with an API to create shipment labels. Moesif has been quite helpful with debugging process.
Shin Ho, Developer
Analyzing API usage patterns
Rev.ai is an automated speech recognition offering by Rev.com for developers that can make audio and video content searchable and accessible. They built rev.ai from millions of hours of human-transcribed content from Rev.com's om-demand audio transaction services. Rev has two primary APIs. One is for rev.ai's speech to text API, which performs automated speech recognition on input audio / video. The other is Rev.com's transcription and caption API, which allows integration with their human transcription and captioning service trusted by over 100,000 customers including Visa, Salesforce, and Disney. In addition to exposing these APIs to customers, Rev also uses these APIs internally for their mobile apps including Rev Voice Recorder and Call Recorder.Read Case Study
Monitoring APIs on AWS Lambda
Everything is going great. I made some enhancements to the headers sent with each request to enable searching on select items and our stakeholders are really enjoying using it.
Jessica Ross, Senior Software Engineer
Debugging Rest API errors
This customer is a web based accounting platform for startup founders and small businesses for bookkeeping, invoicing, payroll, and more based out of Texas. This company has numerous dashbpards, KPIs, and metrics for data driven founders and small business owners rolled up from accounting, business management, and financial analytics. Their customers are also able to talk to a live accountant directly in the platform for responsive accounting and tax services.Read Case Study
Improving API performance
Basepair is a next generation DNA sequencing (NGS) data analytics SaaS trusted by scientists at Harvard Medical School, Rutgers, Boston Children's Hospital, and others. They make NGS data analysis as simple as booking a flight online. Basepair provides a RESTful interface to add new samples, run analysis, download results, among other tasks. Being focused on the scientific medical community, they also provide a Python CLI tool with higher level methods for common activities.Read Case Study
Moesif is a part of my daily flow giving me important insight into our API as well as the consumers of our API.
Jonathan Pickett, Lead Engineer
Monitoring mobile APIs
Prodigy is software platform backed by 8VC, Battery Ventures, SV Angel and CrunchFund for car dealerships to streamline the car purchase process. Their web and mobile apps enables the sales staff to drive a consistent sales process and increase margins. Prodigy developed a REST API to power their mobile and web apps using Node.js and Express and also to connect with over 1,300 lenders which enables them to offer car loans in minutes.Read Case Study