PHYSICAL REASONING & AGENTIC INFRASTRUCTURE

THE HUMAN
INTELLIGENCE
LAYER FOR
ROBOTS & AI.

Softinator AI is an elite foundry specializing in foundation models, coding agents, and physical reasoning (VLAs). Powered by a 47K+ global expert network, we supply high-fidelity human-in-the-loop and spatial teleoperation data for governments and industrial enterprises.

ROS2 NODE SYNC · CONNECTED

SCROLL

Trusted by frontier teams

Precision-engineered models for
cutting-edge teams at

Reasoning in motion

ONE EPISODE. UNDER YOUR THUMB.

SCROLL = SCRUB · REVERSE = REWIND

SCROLL = SCRUB · REVERSE TO REWIND

Operational vision

EXPANDING THE
COGNITIVE ENVELOPE
OF ROBOTICS.

STATE-OF-THE-ART FOCUS

We design training and evaluation programs for generalist policy classes such as π0 and OpenVLA-OFT, with flow-matching action heads, structured reasoning, and safety-aware evaluation for long-horizon industrial tasks.

THE EDGE FOUNDRY

We engineer high-fidelity egocentric and teleoperated data across vendor-neutral bimanual and industrial-arm systems, with synchronized state, action, failure, recovery, and deployment evidence.

Operating model

ONE FOUNDRY.
FOUR LAYERS.

Enter at the data, model, agent, or deployment layer without losing traceability. Security, provenance, independent review, and controlled delivery run through the complete system.

01Layer 01

HUMAN SIGNAL

Expert data & evaluation

Domain-aware creation, annotation, critique, adjudication, and red teaming for logic-dense model behaviours.

STEMCODEVISION

02Layer 02

LEARNING

Pre-training & post-training

Corpus engineering, SFT, preference signals, verifier data, model evaluation, and targeted adaptation.

SFTRLHFEVALS

03Layer 03

SYSTEMS

Agentic applications

Tool-using workflows, software-engineering agents, multimodal task environments, and reliability harnesses.

TOOLSTRACESPOLICY

04Layer 04

PHYSICAL INTELLIGENCE

VLA & embodied AI

Teleoperation, egocentric capture, simulation, robot learning, and edge inference for autonomous systems.

VLASIMEDGE

Our mission

REASONING
IN MOTION.

Softinator AI bridges the gap between first-person visual perception and robotic execution by solving the grounding bottleneck through massive egocentric data pipelines.

AUTOMATED DATA ENGINE

We use model-assisted relabeling and independent review to convert raw spatial teleoperation video into structured training datasets.

47K+ EXPERT NETWORK

A massive, globally distributed workforce of over 47,000 PhDs, professors, and elite developers providing human-in-the-loop expert data and RLHF.

GOVERNED DELIVERY

Security is embedded through least-privilege access, isolated workstreams, role-based review, controlled exports, and traceable quality gates.

Advanced embodied cognition

THE EMBODIED
VLA ENGINE.

System 2 Policy Alignment

We design Vision-Language-Action (VLA) adaptation systems using flow-matching and structured reasoning to map multimodal observations and task instructions into action sequences.

This replaces historical, fragile robotic stacks with a single unified neural policy capable of long-horizon task execution.

Cross-Modal Tokenization

Pixels, linguistic coordinates, and 7-DoF state logs are aligned into a continuous token stream for immediate auto-regressive actions.

Latency-Aware Edge Control

Policy serving is designed around action timing, safety interlocks, observability, human override, and the constraints of the target edge hardware.

Workspace Generalization

Demonstration coverage, simulation variation, hard-negative mining, and recovery evaluation help policies operate across changing objects and layouts.

VLA_NODE_ONLINE // PORT_USB_0

TELEMETRY: ILLUSTRATIVE

Select Natural Language Command

ASSEMBLE DUAL-PLATE CLUTCH AND ALIGN RETAINING PIN

CLUTCH_FLANGE_04[0.245, -0.112]

STAGE: IDLE

CAM_NODE_PRIMARY_RAWSYNTHETIC VIEW

Model Inference Flow

Tokenize Inputs

Policy Cross-Attention

Action Sequence Gen

Joint Pos (DoF)

0.0, 0.0, 0.0, 0.0, 0.0, 0.0

Inference Velocity

0.00 M/S

Applied Force

0.0 NEWTONS

Target Coordinate

[0.245, -0.112, 0.589]

Infrastructure explorer

TWO PILLARS.
ONE UNIFIED ENGINE.

CORE BOTTLE-NECK: THE GROUNDING BOTTLENECK

Robot learning is constrained by the scarcity of high-fidelity physical interaction data. Simulation alone cannot bridge the gap for complex, non-linear manipulation tasks in niche industries.

MODULE_01

Spatial Teleop

Capturing manual dexterity in industrial and laboratory settings through spatial computing, vendor-neutral bimanual teleoperation, and synchronized trajectory review.

Spatial VR Capture

Bimanual Teleoperation

Trajectory QA

MODULE_02

Automated Data Engine

Using foundation VLMs for hindsight relabeling, we automatically transform raw egocentric recordings into cross-embodiment robot-action datasets, drastically reducing the annotation bottleneck.

Hindsight Relabeling

VLM Auto-Annotation

Cross-Embodiment

MODULE_03

Simulation & Sim-to-Real

Using simulation and domain randomization to expand collected real-world data, stress-test policy behaviour, and measure sim-to-real gaps before edge deployment.

NVIDIA Cosmos

Isaac Lab

Diffusion Policies

Core solutions

ARCHITECTING
THE AUTONOMOUS STACK.

// 01 / 04

FOUNDATION MODELS

Custom pre-training and post-training of frontier models on state-of-the-art specialized benchmarks.

// 02 / 04

AGENTIC ROBOTICS

Vendor-neutral robotics data, VLA adaptation, simulation, teleoperation, and edge deployment architecture.

// 03 / 04

ONSITE DEPLOYMENT

Secure, local deployment of specialized 3B parameter models for mission-critical enterprise environments.

// 04 / 04

GOV & ENTERPRISE

Governed AI programs with isolated workstreams, human approvals, red teaming, provenance, and audit-ready delivery.

Operational pipeline

UNIFIED
TRAINING
PIPELINE.

EXPERT DATA & EGOCENTRIC CAPTURE

Mobilizing qualified domain experts for logic-dense post-training signal, and capturing first-person multimodal data through VR and bimanual teleoperation.

47K_EXPERT_NETWORKVR_TELEOPERATIONRLHF_LOGIC

AUTO-ANNOTATION & STRUCTURING

Applying foundation VLMs for hindsight relabeling and exact deduplication. We engineer high-signal corpora free from synthetic noise.

HINDSIGHT_RELABELINGEXACT_DEDUPLICATIONHIGH_SNR

PRE-TRAINING & SFT

Supporting VLA policy classes and coding agents with supervised data, preference signals, recovery curricula, verifier-oriented evidence, and targeted evaluation.

SYSTEM_2_REASONINGSWE_BENCHVLA_SFT

EDGE & CLOUD DEPLOYMENT

Designing secure cloud, onsite, and edge deployment paths with observability, human overrides, safety interlocks, and latency-aware inference.

SECURE_DEPLOYMENTOBSERVABILITYEDGE_INFERENCE

Technical dossiers

ARCHITECTURE YOU
CAN INTERROGATE.

These systems answer questions. Click any stage to open its evidence, or run the whole pipeline and watch the trace stream. Telemetry is representative; the engineering patterns are real.

Reference architecture · CODE

Repository engineering agent

Issue localisation, constrained patching, test construction, and auditable repository-level evaluation.

Tree-sitterCodeQLFirecrackerNix / Bazel

Stage 01 · GRAPH RETRIEVAL

The agent walks a code graph built from AST and symbol indexes, ranking files by relevance to the issue before a single line is edited.

files ranked

3 / 3

index

SCIP + tree-sitter

context

repo-grounded

Pipeline · click any stage to interrogate

Trace · code-pipeline SYNTHETIC

// select a stage or run the pipeline

DELIVERED EVIDENCE

Trace logs · patch diffs · hidden-test evidence · adjudicated resolution

STRATEGIC INITIATIVEMUMBAI REGION // PHASED PROGRAM

SOVEREIGN COMPUTE
FOR THE NEXT WAVE.

Softinator is advancing an AI-ready data-center initiative designed to bring model development, data residency, robotics simulation, and enterprise deployment support closer together.

AI COMPUTE

GPU lifecycle strategy, topology-aware cluster design, checkpoint durability, scheduling, and fleet observability.

POWER & COOLING

High-density electrical planning, liquid-cooling readiness, resilience modelling, and phased capacity design.

SOVEREIGN OPERATIONS

Private model development, controlled data residency, secure tenancy, monitored access, and client-defined retention.

PHASE 01

DILIGENCE

Site, utilities, connectivity, policy, commercial demand, and technical basis.

PHASE 02

PILOT CAPACITY

Validated architecture, anchor workloads, operations, security, and financing.

PHASE 03

SCALED CAMPUS

Phased expansion aligned to power, cooling, utilization, and capital gates.

This is a directional, phased infrastructure program. Capacity, site, hardware, and delivery milestones are subject to diligence and program gates.

Corporate capability dossier

Take the full
foundry with you.

The complete Softinator.ai dossier: frontier engagements, embodied-AI and VLA programs, reference architectures, sovereign infrastructure direction, credentials, and the leadership behind it — in one print-grade document.

FRONTIER ENGAGEMENTSTECHNICAL DOSSIERSSOVEREIGN COMPUTECREDENTIALS & LEADERSHIP

DOWNLOAD THE DOSSIER REQUEST THE CONFIDENTIAL ANNEXURE

2026 EDITION · NDA-SAFE PUBLIC RELEASE

THE HUMAN INTELLIGENCE LAYER FOR ROBOTS & AI.

Precision-engineered models for cutting-edge teams at