Ecue

e:cue, operated by Path Ahead Inc (d/b/a e:cue), combines data engineering, machine learning and agentic AI to unify marketing, enrollment and student lifecycle data for education organizations. Its central product is Cue, an AI analyst that ingests data from a customer's tech stack, cleans and joins it, applies custom machine learning models, and returns insights through natural language, including within tools such as Slack. Stated capabilities include lead scoring and prioritization by intent, multi-touch attribution beyond last click, paid search optimization, lifetime-value analysis, retention risk prediction, and board- or partner-ready reporting.

The company describes a four-stage delivery model — data engineering, ML modeling, analytics, and assessment — in which internal analysts and data scientists build the pipelines and models and then remain involved in running campaigns and outreach alongside the customer's team. Earlier positioning presented e:cue more broadly as a go-to-market business intelligence solution for CMOs and revenue leaders, offering the capabilities of a data engineering and marketing analytics team as an alternative to hiring full-time staff or engaging consultants.

At launch the company framed the problem as businesses being unable to extract value from their data, citing an IBM figure of more than $3.1 trillion in annual U.S. costs from poor data quality, and positioned Cue as agentic AI for shaping go-to-market strategy rather than static dashboards.

Founding story

e:cue was founded by Harsha Mokkarala, previously Chief Revenue Officer, Chief Marketing Officer and Chief Data Scientist at 2U, Inc., where he was credited with leading tenfold revenue growth and scaling digital education programs for universities, and earlier a senior executive at Capital One who worked on the shift from traditional to digital marketing powered by predictive analytics. Mokkarala has said he built e:cue after two decades leading marketing, revenue and data teams and working from dashboards and reporting built on poor-quality data.

Business model

B2B SaaS combined with a services layer: e:cue sells subscription access to its Cue AI analyst alongside a hands-on team of go-to-market analysts and data scientists who build and operate the underlying data infrastructure and models for each client.

Subscription-based B2B SaaS with accompanying data science and analytics services.

Traction

Named customers and references include Boundless Learning, for which e:cue reports enabling 30% marketing efficiency gains along with automated bidding and a new paid-media strategy, and a testimonial from the CMO of RVL Pharmaceuticals. The company reports A/B testing showing Cue's approach is 80% more reliable than working from raw, untransformed data and 30% more efficient through faster results and lower compute costs. The launch release referenced strong early traction without specifying customer counts.