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SovereignMalayalam AI. — Araskova Labs, Kerala.

· About Araskova Labs

The data, benchmarks and models Kerala runs on its own infrastructure.

A founder-owned, fully remote team in Kerala. We measure how leading AI models fail on real Malayalam tasks, build the licensed corpus and benchmarks to fix it, and deploy models that run on-premise.

DataBenchmarksModels

കേരളത്തിൽ നിർമ്മിച്ചത്

Built in Kerala

· 002 — The Lab

We measure where leading AI fails on Malayalam, build the licensed data and benchmarks to fix it, and ship models that run on the institution's own hardware.

  • Measured

    Every claim carries the date we measured it.

  • On-premise

    Models run on hardware the institution owns.

  • Studio-funded

    Client work pays for the research.

· 003 — The problem

Leading AI wasn't builtfor Malayalam records.

General models learn mostly from English and run from someone else's cloud. Kerala's institutions need models that read Malayalam properly and stay on their own hardware.

  1. Misread[01]

    Models misreadMalayalam

    Leading models code-switch, transliterate and invent terms on everyday administrative Malayalam: a ~73% failure rate across four models in our June 2026 benchmark.

  2. Offshore[02]

    Records leavethe building

    Cloud AI means sending citizen and client records to servers the institution doesn't control.

  3. On paper[03]

    Old script stayson paper

    Handwritten and pazhaya lipi registers stay unsearchable, because general OCR wasn't built to read them.

  4. Rented[04]

    You rent whatyou should own

    Per-seat licences and closed weights leave an institution with no model, no data and no way out.

· 004 — Method

From a Malayalam pageto a model you own.

Four stages, the same for every system the lab builds: collect, measure, build, deploy.

രജിസ്റ്റർSRC · LICENSEDDOC 0001 · ML / ENOKDRIFTTRANSLIT.200 QUERIES · 4 MODELSMODEL · MLINSTITUTION NETWORK · ON-PREMISE
  1. Collect01

    A licensed Malayalam corpus

    Start from data we can stand behind

    We gather Malayalam and English text with the source and licence of every document recorded, so a model trained on it is one an institution can actually use.

    • 47.5M tokens · as of June 2026
    • Source and licence per document
    • Corpus datasheet in preparation
  2. Measure02

    A benchmark in real Malayalam

    Find out where models fail

    We score leading models on real administrative Malayalam and record each failure: code-switching, transliteration errors, semantic drift and invented terms.

    • 200 real-world queries
    • 4 leading models · June 2026
    • ~73% failure rate
  3. Build03

    Document AI and assistants

    Build for the failures we found

    Malayalam document AI that reads printed, handwritten and old-script records, and assistants that answer in Malayalam from an institution's own documents.

    • Printed, handwritten, pazhaya lipi
    • Answers grounded in your documents
    • Both in development
  4. Deploy04

    On the institution's own hardware

    Run it where the records are

    Quantized models and pipelines sized for the servers an institution already owns. The records never leave its network, and the code and weights are handed over.

    • On-premise by design
    • Source code and weights handed over
    • No per-seat fees

· 005 — From the Lab

Malayalam AI that runswhere the records are.

Built on our Malayalam corpus and benchmark, and deployed on the institution's own servers.

01 · Lab · OCR and extraction for Malayalam records

Malayalam Document AI

Reads Malayalam documents — printed text, handwriting and old-script (pazhaya lipi) records, forms and registers — and turns them into searchable, structured data. It runs on-premise, so the records never leave the institution.

  • Printed and handwritten Malayalam
  • Old script (pazhaya lipi)
  • Forms and registers to structured data
  • Runs on the institution's own servers

02 · Lab · Malayalam assistants for institutions

Malayalam Assistants

Assistants that answer in Malayalam from an institution's own documents, built on our Malayalam corpus and evaluation work and deployed on infrastructure the institution controls.

  • Answers in Malayalam
  • Grounded in the institution's own documents
  • Evaluated on our Malayalam benchmark
  • Deployed on-premise
· + — Araskova Studio
· + — Open source

· 006 — Research

Four tracksMalayalam AI, measured.

What the lab is working on, with the figures we've measured and the date we measured them. Each track links to its research note.

  1. [01]Malayalam Evaluation Benchmark

    LLM Evaluation · Administrative Malayalam

    MAL_EVAL_BENCH_01INTERNAL · COMPLETE
    050100FAILURE RATE · %

    ~73%

    FAILURE RATE · 4 MODELS · JUNE 2026

    200 real-world Malayalam administrative queries, scored against four leading models in June 2026. Failure means code-switching, transliteration errors, semantic drift or invented terminology.

  2. [02]Corpus Curation & Licensing

    Language Corpora · Malayalam + English

    MAL_CORPUS_LIC_02ACTIVE
    0102030405047.5M · ML + ENM TOKENS

    47.5M

    TOKENS · AS OF JUNE 2026

    A curated Malayalam and English corpus with the source and licence of every document recorded, so institutions can use models trained on it. Details are on the corpus datasheet.

  3. [03]Malayalam Document AI

    OCR · Printed, Handwritten & Old Script

    MAL_DOC_OCR_03ACTIVE
    അPRINTEDകHANDWRITTENൿOLD SCRIPT

    OCR

    PRINTED · HANDWRITTEN · OLD SCRIPT

    OCR and extraction for printed, handwritten and old-script (pazhaya lipi) Malayalam: forms, registers and records turned into structured data, on-premise.

  4. [04]On-Premise Deployment

    Quantized Inference · Institution Hardware

    ONPREM_INFER_04ACTIVE
    INSTITUTION NETWORKCLOUDWORKSTATIONSERVER

    On-prem

    BY DESIGN

    Quantized models and document pipelines sized to run on the servers and workstations an institution already owns, with its data kept on its own network.

· 007 — Who it's for

Made for the peopleand institutions of Kerala.

Malayalam AI is for everyone who reads and writes it, from a student to a district office. Some of it we publish openly; some we build and install for an institution.

  • AI that answers properly in Malayalam, not a translation of English. We test leading models on real Malayalam and publish what we find, so people know which tools they can trust in their own language.

    Our research →
  • Research notes on Malayalam evaluation, corpora and OCR, published as we measure, and a research fellowship for people who want to work on them with us.

    Research fellowship →
  • Open-source tools anyone can use and build on, released every so often under open licences.

    Open source →
  • Read Malayalam files, circulars, registers and case records, and answer staff questions from them, on the department's own servers.

    Talk to us →
  • Turn handwritten Malayalam forms and ledgers into structured data that stays inside the bank.

    Talk to us →
  • Digitise Malayalam patient records and referral letters on hardware the hospital controls.

    Talk to us →
  • Make printed and pazhaya lipi collections searchable, with the source and licence of every document recorded.

    Talk to us →
  • Custom software and AI automation, built by Araskova Studio with direct builder access and no agency markup.

    Araskova Studio →

· 008 — Accepting select commercial & research contracts

Bring us your recordsWe'll say what we can build.

Your records, your hardware, and what the system has to do in Malayalam: that's all we need to start.

hello@araskova.com·+91 62822 37771

  • 100% owned by you

    Source code, model weights and database schemas are yours. No per-seat fees, no lock-in.

  • On-premise

    Runs on hardware inside your institution. Records and files stay on your network.

  • Malayalam-first

    Evaluated on real Malayalam tasks with our benchmark, sized for the hardware you have.