Cresta vs Encord

Conversational research tool: poses natural-language questions over customer interaction data and returns evidence-grounded charts, comparisons and written answers.

Automated 24/7 phone-answering system for small businesses that captures leads, books/reschedules appointments, answers questions and routes calls.

A supervision surface for a contact centre running both people and AI agents, giving real-time oversight and guidance across the two.

Identifies which customer conversations are automation candidates, assigns a readiness score by volume/complexity/resolution rate, and exports discovered flows into Cresta's AI Agent Builder.

Real-time AI that listens to live contact-center conversations and surfaces behavioral coaching, source-backed answers and after-call summaries directly inside an agent's existing tools.

Analyzes 100% of customer conversations across human and AI agents to surface behavioral drivers of CSAT, handle time and revenue, combining Cresta Insights, Quality Management and Coach.

The no-code AI workflow engine that powers every Cresta product ('Opera GenAI Intents, Opera Workflows, Opera Analyzer'), letting contact-center teams configure and continuously optimize AI without writing code.

Continuously listens during customer interactions and surfaces precise answers in real time, grounded in conversation and on-screen context (account status, order history), guiding agents through complex workflows.

Analyzes conversation data to generate realistic customer personas, ranked by traffic volume and traced to source conversations, for AI-agent testing, human-agent training and voice-of-customer simulation.

Lets contact-center agents practice against AI-simulated customers built from real conversations, for onboarding, continuous skill development and targeted coaching.

Data Agents automate Encord data pipelines by integrating humans, state-of-the-art models and a customer's own models into data workflows. They handle tasks such as pre-labeling, object segmentation and tracking, video captioning, audio transcription and sentiment analysis, combined with human-in-the-loop quality assurance.

The multimodal data layer for physical AI: one platform for managing, curating, annotating and aligning sensor, video, image and text data at petabyte scale. The modules a buyer licenses — Annotate, Index and Active — are recorded separately.

Encord Active is Encord's model and data evaluation product. It evaluates and validates models against their data to surface, curate and prioritise the most valuable data for training and fine-tuning, covering model robustness checks, drift and failure-mode detection, automated label-error detection, and active learning workflows across images, video, 3D/LiDAR, audio and documents.

Encord Annotate is Encord's multimodal data labeling product, used to annotate and review images, video, audio, text, documents, DICOM, LiDAR and geospatial data. It provides AI-assisted labeling, customizable ontologies, human-in-the-loop review workflows and quality-control tooling for managing large annotation teams.

Managed annotation service: Encord supplies vetted domain experts for a customer's task and runs the projects, with an evaluation workflow built around the customer's own spec rather than volume alone.

Managed collection of real-world training data for physical AI: in-field operators, teleoperation facilities and configurable lab environments gathering the embodied, egocentric and sensor data a robotics model needs.

Encord Index is Encord's multimodal data curation and management product. It lets teams search datasets with natural language and similarity search across video, image, audio, LiDAR, text, document, geospatial and HTML files, filter by 40+ data metrics and custom metadata, visualise outliers on embeddings plots, and remove duplicates and poor-quality data via Collections. Data stays in the customer's own cloud with 'zero data migration required'.

End-to-end data service for robotics, autonomous systems and embodied AI: data collection (in-field operators, teleoperation), curation, LiDAR/point-cloud/multi-camera annotation, VLA/VLM action-captioning, and post-deployment feedback loops, with on-prem/VPC deployment.