The Dcipher Analytics Platform

A SaaS solution that perfects human-computer collaboration for augmented text analytics

Harnessing the power of natural language processing, deep learning, and visual analytics to extract value from text

Comprehensive data import options

Import data from a range of file formats, more than a thousand APIs, or one of the most extensive social media archives on the internet. Segment, extract and score text units by relevance.

Interactive exploration

Let topics and associations emerge bottom-up and visualize relationships within the data. Iterate with the help of immediate visual feedback. Use document landscapes and token networks to find meaning in large document collections.

Parallelized computation

Speed up the process by leveraging computing that is distributed and fully parallelized in the cloud. Scale up to the number of cores you need to get the job done as fast as you want.

Smart data prep

Merge flat or nested datasets. Standardize inconsistent date formats and use fuzzy matching to merge similar texts. Choose among a number of data cleaning options and resolve ambiguities through visual context filtering.

The best of NLP

Enrich your data through world class sentiment, emotion, entity, and category detection models. Find language independent document and word embeddings using neural networks to capture contextual similarities in your data.

Efficient modelling (Coming Soon)

Train text classifiers through an iterative technique using a combination of supervised and unsupervised machine learning. Save and run your models on unannotated data.

Flexible data structure

Leverage Dcipher’s flexible, nested data structure which incorporates the output of operations. Use data on different levels of the hierarchy without the need for transforming or keeping track of relations between datasets.

Trend & burst analysis

Detect trends and sudden bursts in your data. Identify topics with high momentum and visualize their evolution over time. Forecast future trends using the latest machine learning techniques.

Automation & deployment (Coming Soon)

Build automated workflows and apply your models and operation pipelines on data in streams or batches. Access through Dcipher APIs for use in external applications and dashboards.

Features

Data import and export

  • Import data in various flat and nested formats, including json, csv, tsv, Excel, and plain text
  • Import data from social media
  • Import data from a wide range of public APIs
  • Download data and visualizations

Text wrangling and cleaning

  • Sample and shuffle data
  • Join datasets, both flat and nested
  • Clean text off emojis, URLs, line breaks, XML tags, tabs, punctuation, and any user-specified prefix or substring
  • Standardize date formats
  • Remove or extract duplicates
  • Segment texts into shorter, cohesive text snippets
  • Split texts by pattern
  • Extract patterns and substrings from text
  • Extract dates from text
  • Filter on same level or across levels of nested data structure

Natural language processing

  • Tokenize, lemmatize, lowercase, and remove stop words from text
  • Tag words with their parts-of-speech
  • Find topics and overrepresented words in a set of documents
  • Enrich texts by automatically annotating them with categories, entities, sentiment, and emotions
  • Detect the language of texts and automatically translate them into another language

Quantification and analysis

  • Quantify the occurrence of words
  • Quantify the length of texts in terms of number of characters, words, sentences, and paragraphs
  • Group, aggregate, and run functions on data
  • Tag and annotate individual or groups of documents
  • Calculate links between values and visualize as a network

Search and mapping

  • Search for words and texts based on search criteria or contextual similarity
  • Cluster documents based on similarity into a document landscape
  • Machine learning-based vectorization, dimensionality reduction, and clustering of documents and words
  • Outlier detection
  • Visually inspect and draw conclusions from data

Experience Dcipher Analytics