unleash your genius

Universally Configurable AI Knowledge Engines for Decision Automation

Nebula Social

Viral Narrative Prediction & Automated Content Generation

Nebula Social, seeded with user-defined ground truth, analyzes massive volumes of social media content, predicts emergent viral narratives, and produces viral content, enabling customers to increase reach and influence behavior.

ARGUS

AI That Thinks Before It Speaks

Argus is a versatile AI Agent for anomaly detection that continuously analyzes vast volumes of dynamic open-source unstructured data and autonomously generates knowledge graphs to extract critical insights that bolster national security.

Information overload creates organizational knowledge loss
Information overload causes inaccurate forecasts
Information overload biases decisions
Information overload stifles productivity
Information overload enables bad actors to manipulate behaviors
The Last Mile Problem in AI

Enterprises aiming to integrate proprietary data into large language models (LLMs) are frustrated. Absent a continuously learning semantic layer, it’s difficult for users to find meaningful insights that are not already present in the text.

Infinite prompts, no insights

Without contextual awareness it’s impossible for an LLM to synthesize information across large swaths of document collection. The consequence is time wasted infinitely prompting a chatbot in the hope it will produce useful predictive insight that will never materialize.

Accrete’s Knowledge Engines

Accrete’s knowledge engines autonomously generate knowledge graphs that semantically unify vast document collections, facilitate sequential reasoning, & generate insights that would otherwise require an army of human experts.

Predictive Insight, decision automation

Accrete’s agents produce domain-specific insights that can be embedded into vector databases to not only reduce the prompt space for LLMs but enable LLMs to produce actionable insight to drive automated decision making.

J.P. Morgan:  "In this report, we explore the information contained in earnings call sentiment using novel, alternative data sets. Specifically, we look at the relationship between [Accrete’s model's] sentiment on capital returns and the subsequent dividend futures returns. Our analysis shows that the effects of management sentiment appear to be moderately significant on dividend futures returns in both statistical and economic terms."

Ready to Transcend Your Limits