World's First Video Memory-as-a-Service Platform

Contextual Memory

for your

Videos.

Audio.

Images.

Documents.

Videos.

Audio.

Images.

Documents.

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Capture, connect, and recall organizational knowledge—instantly.

Memory & Context

AI forgets; mem[v] remembers. With continuous context across every modality, your agents gain awareness that lasts—learning from history to act smarter in the moment.

Memory & Context

AI forgets; mem[v] remembers. With continuous context across every modality, your agents gain awareness that lasts—learning from history to act smarter in the moment.

Memory & Context

AI forgets; mem[v] remembers. With continuous context across every modality, your agents gain awareness that lasts—learning from history to act smarter in the moment.

Compound Learning

Like human memory, mem[v] gets smarter with every query and conversation. Patterns strengthen, predictions sharpen, and intelligence compounds over time.

Compound Learning

Like human memory, mem[v] gets smarter with every query and conversation. Patterns strengthen, predictions sharpen, and intelligence compounds over time.

Compound Learning

Like human memory, mem[v] gets smarter with every query and conversation. Patterns strengthen, predictions sharpen, and intelligence compounds over time.

One-time Processing

Connect videos once; mem[v] handles the heavy lifting. We process videos with foundation models, build persistent memory, and serve context at ~500ms forever.

One-time Processing

Connect videos once; mem[v] handles the heavy lifting. We process videos with foundation models, build persistent memory, and serve context at ~500ms forever.

One-time Processing

Connect videos once; mem[v] handles the heavy lifting. We process videos with foundation models, build persistent memory, and serve context at ~500ms forever.

Instant Video Context

After connecting your video sources, mem[v]'s Vison Engine knows about the scenes, products, people, and patterns relevant to your agent without re-processing.

Instant Video Context

After connecting your video sources, mem[v]'s Vison Engine knows about the scenes, products, people, and patterns relevant to your agent without re-processing.

Instant Video Context

After connecting your video sources, mem[v]'s Vison Engine knows about the scenes, products, people, and patterns relevant to your agent without re-processing.

mem[v] is choose-your-own LLM

The memory layer stays constant. The intelligence layer is your choice. No vendor lock-in.

mem[v] is choose-your-own LLM

The memory layer stays constant. The intelligence layer is your choice. No vendor lock-in.

mem[v] is choose-your-own LLM

The memory layer stays constant. The intelligence layer is your choice. No vendor lock-in.

What are we solving

Equip your agents with full contextual

memory in minutes.

Query Memories → Context Engineering

Leverage mem[v]’s powerful data engine to enrich your agent with real-time context from videos, audio, images, documents, and enterprise sources. Retrieve structured results or LLM-ready context for any query in ~500ms.

Continuous Ingestion → Persistent Memory

mem[v] continuously processes your multimedia sources to build a bespoke memory graph. Every video, image, audio file, document, and query improves the memory network with episodic, temporal, and semantic context.

Intelligent Retrieval → Instant Answers

Tap into mem[v]’s persistent memory to instantly surface answers across videos, audio, images, and documents. Find even the smallest details in your video library with precision - 300x faster than re-processing and up to 70% cheaper at scale.

Contextual memory — one command away

# Set your API key as an environment variable
export MEMV_API_KEY="YOUR_API_KEY"

# Import and initialize the client in your Python file
from memvai import MemVClient
import os

client = MemVClient(api_key=os.environ.get("MEMV_API_KEY"))

# Ask context-aware questions
response = client.ask("What did we discuss about improving user retention?")
print(response)

# Set your API key as an environment variable
export MEMV_API_KEY="YOUR_API_KEY"

# Import and initialize the client in your Python file
from memvai import MemVClient
import os

client = MemVClient(api_key=os.environ.get("MEMV_API_KEY"))

# Ask context-aware questions
response = client.ask("What did we discuss about improving user retention?")
print(response)

# Set your API key as an environment variable
export MEMV_API_KEY="YOUR_API_KEY"

# Import and initialize the client in your Python file
from memvai import MemVClient
import os

client = MemVClient(api_key=os.environ.get("MEMV_API_KEY"))

# Ask context-aware questions
response = client.ask("What did we discuss about improving user retention?")
print(response)