Overview
ANIMAS — the Artificial Neural-Intelligence Modular Analytics System — is Zapata AI’s tactical-edge, multi-intelligence generative-AI platform. It ingests heterogeneous mission data, runs on Nvidia GPU hardware, and lets operators and analysts “talk to the data” in natural language. ANIMAS is designed to be useful at the point of decision: in a vehicle, on a pack, or in a deployed TOC — not only back at a CONUS data center.
Let AI draw the connections, evaluate the options, and guide the operator through the critical aspects of a mission — with speed, accuracy, and efficiency — while keeping the human decision-maker firmly in control.
Architecture
ANIMAS is an intuitive AI/ML software stack defined on Nvidia GPUs. It scales through customer-defined combinations of microservices, each targeted to a specific mission payload. The core platform handles data ingestion, entity resolution, retrieval, and model hosting; microservices add the mission-specific logic on top.
Microservices model
Mission capability in ANIMAS is a microservice, not a hardcoded feature. Customers choose which bundles to load — CBRNE, offensive cyber, site exploitation, and others — and the platform composes them at run time. New mission loads are introduced as digitally signed, encrypted payloads, so the integrity chain is preserved across the supply-chain boundary.
Field reconfiguration
Operators can load microservices themselves, without administrator or maintainer assistance. That means units can alter the device’s mission posture to address the problem in front of them — without waiting for a sustainment window. This is one of the core design goals of ANIMAS: the field-deployed team should not need a data-center engineer to change what the platform does.
Security and accreditation
The ANIMAS platform is pre-accredited. Mission-specific payloads are signed and encrypted, and the accreditation model is structured so that loading a new payload does not require a full re-ATO of the base system. This dramatically reduces the fielding timeline compared with a monolithic, per-mission accreditation approach.
Use cases
CBRNE response
ANIMAS’s CBRNE payload fuses chemical, biological, radiological, nuclear, and explosive detector outputs with contextual intelligence to narrow the hypothesis space and surface the right response SOP in real time. Human-on-the-loop throughout. See the CBRNE capability page for more detail on how we structure the decision loop.
Offensive cyber
Offensive-cyber payloads use ANIMAS’s multi-int fusion core to correlate signals, infrastructure, and exploitation evidence, and to present tasking options to the operator with the underlying indicators attached. The goal is tempo: compress the time between signal and action while preserving a clean evidence record.
Site exploitation
On-site exploitation — triage and extraction of digital and physical evidence from a captured location — is time-critical and information-dense. ANIMAS helps the team structure what they find, run entity resolution against prior intelligence, and produce a chain-of-custody-ready record before leaving the site.
Why ANIMAS
| Dimension | Conventional approach | ANIMAS |
|---|---|---|
| Deployment | Reachback to CONUS data center | Runs on Jetson / DGX-form-factor at the edge |
| Reconfiguration | Maintainer-assisted re-image | Operator-loaded signed microservice payloads |
| Accreditation | Re-ATO per mission change | Pre-accredited base; payloads ride the existing ATO |
| Interface | Structured query / dashboards | Natural-language query over fused multi-int |
| Data treatment | Ingest strips provenance | Classification, source, and confidence preserved end-to-end |
Request a capability briefing
For a capability briefing, teaming conversation, or to discuss an OTA/SBIR engagement, request a capability briefing. Our UEI is GFZKSR92ELT6 and our CAGE code is 84JL2.