BuildBetter

Introducing

Artificial Business Intelligence

AI wasn't an afterthought. BuildBetter was one of the first B2B GPT-powered tools back in 2020, and we're building the first ABI.

We bet in 2020:

Remote and hybrid work would create an unprecedented data set. For the first time, every customer call, every internal conversation, every decision would be captured—turning company activity into company knowledge.

AI would get good enough to solve real business intelligence problems, answer meaningful questions, and reduce operational work by at least 70%.

The businesses that survive will be customer-led. As AI raises the bar, only organizations that truly listen and respond to their customers will thrive.

receipts

Everyone claims to be different.
We have receipts.

2020

First (GA) GPT powered B2B Saas tool for teams

2021

First GPT powered call summaries

2022

First GPT powered product documentation tool

2023

First privacy focused features for embedding data into LLMs

2024

First unified analysis engine with cite-able extractions (Signals)

First MCP powered qualitative analysis tool

2025

First automated close the loop workflows

First fully agentic analysis tool with the largest qualitative context window

2026

First fully agentic qualitative analysis chat with MCP access

First vibe building tool for reports, workflows and dashboards

What is ABI?

Defining Artificial Business Intelligence

ABI is an AI's ability to perform emergent business tasks as well as it's ability to interact with the world independently of intervention by other intelligence. This doesn't have to be "superintelligence," could just be Tom, from accounting.

BuildBetter's ABI Flywheel
ABI Flywheel: Integrations → Signals → Workflows → Directional Adaptive Scrutiny → Agent Layer → Multi-Tiered Memory → Custom Context + Propagation → Outputs → Feedback Loop

Directional Adaptive Scrutiny

The interplay between environmental challenges and dynamic cultural (company) scrutiny, which together create a unique evolutionary pressure that drives adaptation and innovation.

Multi-tiered Memory System

A more human-like memory system with short-term, medium-term, and long-term memory capabilities, along with the ability to selectively forget and compress knowledge, enabling faster adaptation and decision-making without being paralyzed by perfect recall or the "Burden of Knowledge."

Propagation

Specialization through division rather than multiplication, promoting efficiency and adaptability by refining specific tasks instead of creating unnecessary complexity or generalization.

These key pillars are what we believe can create ABI

Directional Adaptive Scrutiny

A dynamic feedback loop where the AI continually adapts its decisions by weighing both environmental challenges and cultural (company) shifts—just like how we adjust our choices based on the world around us.

Flywheel
Directional Adaptive Scrutiny flowchart

Environmental Variability

The diverse, cyclical, and sometimes extreme conditions that challenge a system, providing the impetus for adaptation and innovation.

Enhances adaptability to change

Dynamic Selection Criteria

Ever-changing standards for evaluating the success or failure of adaptations, analogous to shifting cultural preferences or evolving fitness landscapes in nature.

Improves decision accuracy
Aligns actions with goals

Recursive Feedback Loops

Self-reinforcing cycles where the outcomes of adaptations influence both the environment and the selection criteria, leading to continuous refinement and meta-learning within the system.

Enables continuous improvement

Multi-tiered Memory System

Imagine an AI memory that works like ours, with short-term, medium-term, and long-term layers—letting it learn quickly, adapt swiftly, and make smart decisions without getting swamped by too much information.

Flywheel
Multi-tiered Memory System flowchart

Multi-tiered Memory System

Short-term memory (RAM), Medium-term memory, Long-term memory ("Lava")

Reduce operational time

Adaptive Learning and Forgetting

Ability to quickly learn from new situations

Selective forgetting and compression of information

Balancing perfect recall with the "Burden of Knowledge"

Prevents information overload
Ship products that drive revenue

Contextual Decision Making

Utilizing different memory types for different decision contexts

Balancing rationality with intuition

Adapting decision-making processes based on the specificity and criticality of information

Increases relevance of actions

Propagation

Propagation involves the agent creating specialized sub-agents through division when necessary—specifically for repetitive or novel and high-risk tasks—to enhance efficiency and adaptability by refining specific tasks rather than adding unnecessary complexity.

Flywheel
Propagation flowchart

Repetitive Task Specialization

Short-term memory (RAM), Medium-term memory, Long-term memory ("Lava")

Reduces time on routine tasks

Risk Management

Ability to quickly learn from new situations

Selective forgetting and compression of information

Balancing perfect recall with the "Burden of Knowledge"

Improves decision reliability
Ship products that drive revenue

Propagation Decision

Utilizing different memory types for different decision contexts

Balancing rationality with intuition

Adapting decision-making processes based on the specificity and criticality of information

Enhances scalability of systems

BuildBetter Business Intelligence Flywheel

By capturing not just what your customers say but also what your team contributes, BuildBetter leverages Directional Adaptive Scrutiny, a Multi-Tiered Memory System, and Propagation to help your team understand the who, what, why, and how of everything you work on—creating an AI that dynamically adapts, learns efficiently, and specializes effectively to revolutionize your business operations.

Dynamic Adaptation Enhances

  • Improves responsiveness by continually adjusting to environmental changes and internal feedback.
  • Aligns decisions with business goals through adaptive scrutiny, leading to innovative solutions.
Reduce operational time

Efficient Learning Improves Decision Quality

  • Accelerates learning processes using a human-like memory system that prevents information overload.
  • Enhances problem-solving efficiency by making contextually relevant decisions based on appropriate memory tiers.
Simple to use to get outcomes
Ship products that drive revenue

Specialization Boosts Efficiency and Scalability

  • Optimizes resource allocation by creating specialized agents for specific tasks through propagation.
  • Increases operational efficiency and enhances scalability by refining tasks rather than adding complexity.
Align teams around problems

The future of business intelligence is here.

Join the teams already using ABI to stay ahead. Be among the first to experience what's next.