Cresta vs Toloka

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.

An independent evaluation platform that ranks frontier LLMs on agentic tool-use tasks using private, non-contaminated benchmarks across industry domains, scored on a pass^5 reliability metric, with the underlying RL Gyms and evaluation datasets available to license.

A self-serve service that lowers per-request inference cost through two tools - fine-tuning LoRA adapters on frozen Qwen3 base models to replace a frontier API on a narrow task, and prompt gisting that compresses long instruction prefixes into learned tokens.

Toloka's catalogue of ready-made training datasets sold outright — three named at the time of writing (Tau-bench Dataset Extension, University-level Math Reasoning, Multimodal Conversations) — as distinct from the custom data work its Platform sells.

Human-in-the-loop data programs -- demonstrations, annotation and evaluation -- for training robotics and physical AI systems.

A self-serve platform where an AI agent turns a described data goal into a full human-annotation pipeline - RLHF and preference data, data collection, instruction tuning, model evaluation, synthetic-data validation and content-moderation QA - with LLM-based quality checks on the output.