Emite Advanced CX analytics (public)

My main use case for eMite is real-time contact center performance management. eMite is built specifically for contact centers with CX teams that need one dashboard to see everything happening right now, not yesterday's report. Three core ways teams use it include live wallboards and dashboards, which display real-time metrics like calls in queue, agent status, SLA, AHT, and abandon rate. The idea is that managers and agents see performance at a glance on TV screens or desktops, eliminating the need for refreshing spreadsheets. Unified data aggregation pulls data from ACD, IVR, CRM, WFM, chat, and email into one place, so instead of logging into five tools, you get a personalized view for both business users and IT. The other core way is reporting with scheduling, publishing reports to the web, PDF, scheduled discovery, and versioning, rated ten out of ten for report versioning.

A quick example of how my team has used eMite for real-time contact center management is during a Monday morning spike. Before eMite, a contact center manager only saw all data in hourly reports from their ACD. At Monday nine a.m., there is a call spike of forty percent and queues ballooning, but they do not know until the ten a.m. report, by which time twenty plus customers have already abandoned. With eMite's live wallboards, at nine-oh-three a.m., the eMite dashboard shows calls in queue jumping from five to twenty-eight in three minutes. SLA drops from eighty-five percent to sixty-two percent in real-time. At nine-oh-five a.m., the supervisor sees the agent status panel where four agents are in after-call work and two are logged out for break. By nine-oh-six a.m., the manager messages the team lead to pull ACW agents back to work and push breaks for fifteen minutes while also rerouting overflow calls to a backup team using the unified view. At nine-twenty-five a.m., the queue is back under eight, and SLA climbs back to over eighty percent.

Beyond the main live wallboard for calls use case, my team leverages eMite in a few other smart ways. The first one is creating personalized executive and agent views, which provide the same data but from different lenses.

eMite has positively impacted my organization in several ways. First, there is a faster time to insight. Previously, we had to wait for end of day or early ACD reports, but with live data, users call this the biggest win since problems get fixed within minutes instead of hours. We experience less abandoned calls, and SLA is recovered faster. Second, there is significant time saved on reporting, with a rating of ten out of ten for report versioning and publishing to PDF, as teams claim they eliminate manual Excel work and repetitive emailing. Reports auto-generate and auto-send to executives, giving us hours back each week. Third, there is better KPI alignment; having a single source of truth is crucial, as everyone from agent to executive sees the same live numbers, reducing disputes and speeding up decisions. Lastly, personalized performance tracking is invaluable; agents can see their own AHT, adherence, and CSAT versus team averages updating live, and users report that adherence improves simply from this visibility, with no manager lectures needed.

The best features eMite offers include real-time reporting with live dashboards, where users rate it nine out of ten. This feature shows calls in queue, agent status, SLA, and AHT live without refresh lag. This is why contact centers use it; they see problems while they are happening, not in tomorrow's report. Another great feature is the granular drill-down analytics, allowing clicks from the overall SLA of seventy percent down to the specific queue, agent, or call, which users say is a killer feature. The third one is report automation, allowing publishing to PDF with a rating of ten out of ten, and report versioning also rates a ten out of ten, while scheduled delivery is rated nine out of ten. By setting it once, the team can automatically email executive SLA PDFs every eight a.m. and post agent scorecards to the web portal every Friday, which eliminates manual work and Excel exports. Lastly, the personalized views are for everyone; the same platform provides different dashboards for executives, supervisors, agents, and IT, so everyone has tailored access whether on TVs, tablets, or desktops.

The feature that has made the biggest difference for my team is the real-time dashboards with granular drill-down capabilities. Users say it beats everything else because of the speed to fix problems. In the old way, one would see the SLA crash in tomorrow's report, and the damage is already done. With eMite, at nine-oh-three a.m., when the queue jumps from five to thirty, I can drill down and discover four agents are stuck in after-call work, allowing us to fix it by nine-ten a.m. This shift from reactive to proactive management is what users call the aha moment. Additionally, having one screen eliminates tool hopping; previously, managers had ACD, WFM, CRM, and Excel open, but now all data is fused with personalized views. Executives see high-level SLA, supervisors see agent-level details, and agents see their own scores, which leads to less time hunting data and more time fixing issues. Lastly, it changes behavior because it is live and shown on TV screens, prompting supervisors and agents to actually watch it. When teams see their own AHT versus team averages updating live, adherence improves without us saying anything. Visibility itself drives performance.

There are a couple more aspects users find valuable that often do not get talked about. First, eMite runs on browsers, which means no IT headaches from software installs, operating seamlessly on wallboards, TVs, agents' desktops, and managers' iPads. IT teams appreciate that updates occur server-side, alleviating the concerns associated with desktop BI tools. Second, the APIs for embedding are rated highly, with both REST API and JavaScript API allowing teams to embed eMite widgets into existing portals or CRMs, so supervisors do not have to log in again; the metrics can live inside whatever platform they are already using, such as Salesforce or Zendesk. Lastly, I find the predictive analytics to be less hyped than real-time but useful, as it can forecast queue times and SLAs based on current trends. For example, it can indicate that at the current rate, we will miss the SLA in twenty-two minutes, prompting us to staff up before the problem arises.

If I talk about features or aspects that need improvement, the first concern is information overload and dashboard clutter. The biggest complaint I hear is that the dashboard contains so much data that new users often feel overwhelmed. Even though it is rated eight out of ten for data discovery, users suggest better ways to hide or filter metrics until needed. Best practices suggest that successful teams start with three to four KPIs on their wallboard and then add more later. Another improvement users wish for is audio alerts; they want sound notifications when calls hit a queue or SLA drops. Currently, it is visual-only, necessitating constant screen monitoring, which can be a gap for busy supervisors. Third, the interactive data visualization layer scores eight out of ten, but users request more interactive charts. Currently, it is clean and efficient, yet lacks the drag-and-drop explorability of Tableau or Domo. Additionally, there is mention of enterprise scalability; eMite users state that while it is well-suited for small to mid-scale companies, it struggles with large companies that have huge data volumes, often resulting in performance issues and dashboard load complications. The mobile app is another area of improvement; while it is good, some users request more admin controls via mobile, as it is currently better for viewing and drill-down rather than configuration changes. Lastly, the learning curve for custom KPIs also needs attention.

Regarding additional needed improvements, the custom KPIs feature is a strength but setting them up is not plug-and-play. Non-analyst users sometimes require assistance from the IT data team to construct formulas. Furthermore, the alert system is the most common request, with users desiring configuration for audio alerts and push notifications when queues exceed a certain number of calls, SLAs drop below a specific percentage, or when agents are not ready for too long. Currently, it is visual-only, causing supervisors to potentially miss spikes if they momentarily look away from the wallboard. Additionally, customizing dashboards for non-technical users presents challenges; while the drill-down feature is powerful, building custom dashboards and KPIs involves a learning curve. Teams seek more drag-and-drop widgets and templates; at present, IT data folks typically need to set this up and then hand it off.

I have been using eMite for the last four years.

I wish I could give you the exact time saved or percentage improvement, but based on eMite's review at TrustRadius, the data indicates that we have seen up to a twelve percent improvement in SLA and an eighteen percent reduction in abandoned calls per month. However, the feedback focuses more on qualitative outcomes, such as real-time visibility and granular drill-down capabilities rather than hard percentage numbers. Users report substantial time savings due to the ten out of ten rating for report versioning, mentioning hours saved weekly by eliminating manual Excel exports and repeated emailing, but no exact hours are listed. Users state that eMite is designed for real-time querying and personalized views for business and IT, emphasizing that the shift is from reactive to proactive resolution of queue spikes, now fixed in minutes as opposed to discovering them in the next day's report.

If I offer advice to others considering using eMite, I suggest starting with their real data rather than demo data. eMite's strength lies in granular drill-down capabilities with real-time accuracy, and the only way to build trust in the system is to connect your actual ACD with your CRM for one week. If SLA, AHT, and abandonment numbers align with your source systems, you are good to go. Additionally, it is essential to test the two major issues most users complain about: dashboard overload and the absence of audio alerts. I suggest that when opening the dashboard with a new supervisor, if they feel overwhelmed within five minutes, plan to develop filtered role-based views upfront rather than showing fifty KPIs on day one. Finally, ensure that the deployment is based on compliance priorities first. For AWS customers, using the Marketplace will streamline procurement while providing consolidated billing, and you receive cloud formation for your specific cloud environment.

If I talk about final points regarding eMite, I would summarize it as follows. It is a browser-based CX analytics tool specifically designed for contact centers, effectively eliminating Excel and manual reporting. It pulls ACD, CRM, and IVR data into live dashboards with drill-down capabilities. Users rate it nine out of ten, reflecting a nine percent score above the category average on TrustRadius. eMite is a great fit for small to mid-market contact centers, particularly for Amazon Connect users and teams needing live SLA and agent visibility without requiring a data engineering team. Users also mention that it is not ideal for very large enterprises due to scaling issues. It possesses commendable AI capabilities, provides substantial security and governance, and can be deployed as a public cloud SaaS, private cloud, on-premises, or hybrid. It is readily available on the AWS Marketplace. I would rate eMite nine out of ten overall.

Public Cloud

Amazon Web Services (AWS)

What do you like best about the product?

What I like best about Prophecy is its code-first approach combined with a clean visual interface for building Spark and data engineering pipelines.
It gives engineering teams more flexibility and control while still improving productivity and collaboration.
Compared to heavier platforms, it feels faster, more modern, and better suited for hardcore technical teams working directly with cloud data stacks.

What do you dislike about the product?

One thing I dislike about Prophecy is that some advanced features and integrations still feel less mature compared to larger enterprise platforms.
Debugging complex pipeline issues can sometimes be less intuitive, especially in hybrid visual/code workflows.
It also has a learning curve for teams that are new to Spark or modern cloud-native data engineering practices.

What problems is the product solving and how is that benefiting you?

Prophecy solves the problem of slow, manual, and hard-to-maintain data pipeline development by combining visual design with code-first engineering.
It benefits me by speeding up Spark pipeline development, improving collaboration, and generating cleaner, production-ready code.
The platform also helps reduce repetitive engineering work while still giving technical teams flexibility and control over their data workflows.

What do you like best about the product?

The load completion board is easy to understand from a visual glance

What do you dislike about the product?

It can be encumbering to find a process because of the different windows that are needed instead of being a more direct pathway

What problems is the product solving and how is that benefiting you?

It is helping our team optimize route creation times which allows synergy's to be created within other areas of opportunity

What do you like best about the product?

Prophesy helps us manage our fleet of 40 trucks. We use it to dispatch and route plan.

What do you dislike about the product?

Although very useful and essential, Prophecy appears to be outdated and a lot of the advanced features are difficult to figure out and often require us to reach out to support.

What problems is the product solving and how is that benefiting you?

Prophecy helps us manage our loads from the time we receive them to the time that we deliver them. We use it to help plan trucks, and we use it to collect data to bill customers.

What do you like best about the product?

I really like the niche and elegant ui of prohecy, via prohecy we can connect the dots between various soruces and destination, it provides a various number of transformation like join,split, api enrichment etc.. Apart from this,I really like the logging feature as well. It's column lineage feature set it apart from other etl platform

What do you dislike about the product?

Sometimes it is difficult to identify root cause of pipeline feature due to sudded restarts loop of a job, so we need to deep dive into pipeline logs to find it. Also some topics in documentation can have more real life examples to enable user to use and apply them in the pipeline

What problems is the product solving and how is that benefiting you?

With prophecy and databrick integration, we are able to schedule 1k+ databricks jobs using prophecy scheduler. Our jobs consists of bronze to silver etl, qc jobs, gold flatten jobs and some realtime spark streaming jobs as well. With prohecy we are able to properly utilize databricks resource. It provides a lot of insights of data using custom transformation which enable our downstream team to quickly research on user trend on our platform which ultimately increase user churn rate on our platform

What do you like best about the product?

It provides easy to use visual editor, It generates open source format code, No vednor lockin, Automated release management.

What do you dislike about the product?

It doesnt works with Serverless spark clusters yet.

What problems is the product solving and how is that benefiting you?

Prophecy visual editor makes it very easy to write ETL jobs and test them.

What do you like best about the product?

good tool for begineers in programming.

What do you dislike about the product?

recommendations in programming can be improved.

What problems is the product solving and how is that benefiting you?

Abinitio migration to open source Spark.

What do you like best about the product?

Automatically generating code without writing any code manually.

What do you dislike about the product?

In terms of connecting inputs for join it's difficult to understand which datasets are connecting.
The syntax for prophecy is difficult comoared to scala syntax.

What problems is the product solving and how is that benefiting you?

Converting ab initio code into scala/spark code.

What do you like best about the product?

Best UI Experience
Best Support Team
High quality generated code

What do you dislike about the product?

Debugging is difficult sometimes
some amount of learning is required to use this product

What problems is the product solving and how is that benefiting you?

Migrating Abinitio code to Spark code

What do you like best about the product?

Easy UI based development
Automated tools to deploy to AWS and Azure cloud env
Good product support

What do you dislike about the product?

Sometime dedugging is difficult from Prophecy UI.

What problems is the product solving and how is that benefiting you?

It helping us to migrating the applications from Ab Initio to Spark