You’ve built a complex multi-agent system. Agent A is halfway through a 5-minute research task. It's found the data, it's starting to synthesize it... and then the heartbeat stops.
Maybe the spot instance was reclaimed. Maybe the Python process OOM'd. Maybe the network hiccuped.
In 99% of frameworks today, that agent is gone. The context is vaporized. You have to restart from the beginning, wasting tokens, time, and money.
We built Engram because we believe agents shouldn't be fragile scripts. They should be Indestructible Processes.
The Mid-Step Miracle: Temporal Recovery
Most "memory" in AI is just a database table of chat logs. That’s not enough.
Engram uses Event Sourcing with Temporal Context. Every thought, tool call, and observation is an immutable event with a nanosecond-precision timestamp. When an agent is replayed after a crash, it doesn't just see what happened—it sees when it happened, relative to the now.
This prevents "temporal amnesia" where agents lose their sense of time during recovery loops.
The Sandbox: Running Agents at "Level 0"
Safe execution of agent-generated code remains the "Holy Grail" of AI security.
When an Engram agent calls a tool, it initiates a WASM-based Sandbox (powered by wazero). We call this "Containerization at the Function Level."
- CPU & Memory BoundsStrictly limit how much resource a tool can consume.
- Filesystem IsolationTools have zero access to the host machine.
- Dynamically PluggableJust drop the .wasm binary into the engine's tools/ folder.
Built for the "Token-per-Second" Era
We built the core engine in Go for one reason: Performance is UX.
In the world of streaming LLMs, every millisecond of overhead is a second of user frustration. By using gRPC bidirectional streams and a high-concurrency Go runtime, we’ve achieved:
🐍 Python SDK: The Human Interface
You don't need to know Go to use Engram. Our Python SDK is designed to feel like a native extension of your existing stack.
from engram.v1 import agent_pb2, agent_pb2_grpc
# Create a 'Ghost in the Machine'
resp = stub.CreateAgent(agent_pb2.CreateAgentRequest(
goal="Deep research into the local supply chain.",
model="llama3.1:70b"
))
agent_id = resp.agent_id
# Chat with a stream that never dies
for msg in stub.Chat(generate_messages(agent_id)):
if msg.HasField('text'):
print(f"[RECOVERABLE] Agent says: {msg.text.content}")The Future of Persistent Intelligence
We are moving away from "Chatbots" toward Autonomous Colleagues.
A colleague doesn't forget your name when the Wi-Fi drops. A colleague doesn't lose their progress on a report because the computer restarted.
By giving AI a durable identity, Engram is shaping a future where agents are as reliable as the servers they run on. We are building the operating system for the next generation of digital workers.
Stop building ephemeral experiments.
Start building agents with a soul.