01
Transform
Move information between formats, systems, and delivery requirements.
- Document and data conversion
- Legacy system migration
- Bulk document generation
- Image, video, and audio transformation
Tara Compute
From raw material to useful output.
Tara Compute transforms documents, data, images, video, and audio through workflows built around the result your business needs.
Explore capabilities
⚡ Tara Compute Open-Source Core
Taraference (`tarafer`)
An open-source, multi-turn GGUF inference engine engineered in Rust for maximum single-stream decode speed on NVIDIA GPUs. Features packed Q4_K/Q6_K × Q8 DP4A kernels, CUDA graphs, and cooperative in-block reduction.
- Single-stream decode optimized for maximum tokens/sec
- Built-in OpenAI-compatible API server (`--serve`)
- Runs on local hardware (T4, 3050 Ti, A10) with dynamic NVRTC
tarafer — quickstart
LINUX & WINDOWS# 1. Download & install prebuilt binary
curl -fsSL -o tarafer-linux-x86_64.tar.gz https://github.com/agkomyint/taraference/releases/latest/download/tarafer-linux-x86_64.tar.gz
tar -xzf tarafer-linux-x86_64.tar.gz && ./tarafer install
# 2. Download model & run interactive chat
tarafer --download 0.5b
tarafer models/Qwen2.5-0.5B-Instruct-Q4_K_M.gguf
# 3. Or launch OpenAI-compatible server
tarafer models/Qwen2.5-0.5B-Instruct-Q4_K_M.gguf --serve
Listening on http://127.0.0.1:8787 (/v1/chat/completions)
What Tara Compute does
A complete path through the work.
The service can handle a focused transformation or connect several stages into one production workflow.
02
Extract and understand
Turn unstructured material into information people and systems can use.
- Structured data extraction
- Summaries and action items
- Classification and tagging
- Cross-media extraction
03
Standardize and validate
Make inconsistent data reliable, comparable, and ready for delivery.
- Cleanup and normalization
- PII redaction
- Data mapping and canonical schemas
- Schema validation and QA
04
Compute at scale
Run compute-heavy work across archives and high-volume pipelines.
- Video understanding and indexing
- Embeddings for semantic search
- Synthetic data generation
- Similarity-based deduplication
Cross-media workflows
One pipeline, not a chain of handoffs.
A raw recording can become a transcript, a summary, tagged action items, and a structured spreadsheet without splitting the work across separate tools.
RecordingTranscriptSummaryStructured output
Compute-heavy work
For workloads that stop being scripts.
Large archives introduce throughput, batching, quality control, privacy, and cost questions. Tara Compute treats those as part of the system.
LLM Serving via Taraference
Ultra-fast single-stream CUDA decode and OpenAI-compatible GGUF serving.
Video archives
Searchable indexing across large footage libraries.
Semantic search
Embeddings for enterprise search and RAG.
Synthetic data
High-volume generation with quality controls.
Similarity search
Near-duplicate discovery across large datasets.
Cross-media pipelines
Unified extraction across audio, video, and text documents.
Start with the problem
Tell us what needs to happen at scale.
We will review the use case, talk through the data and output, and decide together whether Tara is the right fit.
Tell us the workload, quality bar, and delivery requirements. We will shape the right project around it.