analytics / overviewLIVE

Tokens

910.5K

Messages

3.6K

Documents

Total Memories

Activity

Prompts and tokens used (auto-grouped)

anthropic.claude-opus-4-6-v1gpt-5.4gpt-4oanthropic.claude-opus-4-8gpt-4.1

Apr 12May 10Jun 07Jun 21

Memory Calls Over Time

Read and write operations trend

Reads Writes

Apr 12May 10Jun 07Jun 21

Top Models

Most used models by count

910.5KTotal Tokens

anthropic.claude-opus-4-6-v1

aws-bedrock · 10 calls

909.2K

gpt-5.4

openai · 1 calls

1.1K

gpt-4o

openai · 1 calls

anthropic.claude-opus-4-8

aws-bedrock · 1 calls

gpt-4.1

openai · 1 calls

API Calls

AI infrastructure delivered through a unified API

Backboard gives organizations one configurable infrastructure layer for running AI across cloud, private cloud, on-premise, and on-device environments.

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Build AI without rebuilding the stack

Most AI teams start with a model API.

Then they add memory. A vector database. A retrieval layer. Routing logic. Prompt management. Agent frameworks. Evaluation tools. Monitoring. Security controls. Deployment infrastructure.

Over time, what looked like a feature becomes a fragmented AI stack that is expensive to operate, hard to secure, and difficult to change.

Backboard brings those core capabilities together behind one unified API.

Use the models you want. Deploy where you need. Keep control over your data, infrastructure, and architecture.

Over time, what looked like a feature becomes a fragmented AI stack that is expensive to operate, hard to secure, and difficult to change.

Backboard brings those core capabilities together behind one unified API.

Use the models you want. Deploy where you need. Keep control over your data, infrastructure, and architecture.

Over time, what looked like a feature becomes a fragmented AI stack that is expensive to operate, hard to secure, and difficult to change.

Backboard brings those core capabilities together behind one unified API.

Use the models you want. Deploy where you need. Keep control over your data, infrastructure, and architecture.

Build AI without rebuilding the stack

Most AI teams start with a model API.

Then they add memory. A vector database. A retrieval layer. Routing logic. Prompt management. Agent frameworks. Evaluation tools. Monitoring. Security controls. Deployment infrastructure.

Model routing

State

Memory

RAG

Embeddings

Tool calling

Multi-agent

Context

BACKBOARD.IOSINGLE UNIFIED API

17,000+ LLMsMULTI-PROVIDER

Persistent state managementZERO-CONFIG

Native memory (Lite & Pro)AUTO-EXTRACT

RAG + document processingHYBRID SEARCH

Embeddings built-inSWAP-FREE

Tool calling & parallel executionNATIVE

Multi-agent + portable memoryCROSS-AGENT

Adaptive context managementAUTOMATIC

DIY STACKYOU GLUE IT ALL TOGETHER

LiteLLM / OpenRouterSELF-MANAGED

Redis / PostgresDIY SCHEMA

Mem0 / Zep / customCOMPLEX SETUP

Pinecone + LlamaIndexMANUAL TUNING

OpenAI / Cohere EmbeddingsSEPARATE BILLING

01

Cloud

Use managed infrastructure and access leading frontier and open models without locking your applications to a single provider.

02

Private cloud

Deploy within your own cloud environment with stronger control over networking, access, data boundaries, and architecture.

03

On-premise

Run AI inside your own infrastructure for sensitive workloads, regulated operations, and systems that cannot depend on external services.

04

On-device

Deploy optimized models on laptops, workstations, edge hardware, and field devices for lower latency, stronger privacy, and resilient disconnected operation.

Designed for organizations, not demos

Backboard is built for teams that need AI systems to perform beyond a prototype. Use the platform to build:

01

Private enterprise copilots

02

Internal knowledge and search systems

03

AI workflow automation

04

Agent-based operational tools

05

Document intelligence systems

06

Customer-facing AI applications

07

Secure development environments

08

Government and regulated-sector AI deployments

Build AI on infrastructure you control.

Deploy advanced AI with more flexibility across models, data, hardware, and environments.

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