LLM and GPT-like Development Services for Enterprises

LLM Development

Harness the transformative power of Large Language Models (LLM)s and Retrieval Augmented Generation (RAG)s to build enterprise-ready AI applications that are robust, factual (no model hallucination!), and production-ready.
sectors ai search

Custom LLM for Leading Enterprises

Clients like BPK (Badan Pemeriksa Keuangan), State-owned enterprise PT.PP, DSN Group and Canada-based Daita Inc have all counted on Supertype to build custom generative AI solutions that combine proprietary data with leading LLM models tailored to their needs.llm vendors

Bespoke LLM Solutions

...with Supertype as a consultant since 2020the company reduces their operational costs by 35%
AI Generation & Summarization

Build custom AI models trained on your company's data to generate summaries from Standard Operating Procedures and Knowledge Base.

 ?
 ?
Make Everything Search-able

Turn proprietary documents, emails, chat logs, PDFs, and spreadsheets into LLM-ready vector stores for querying and analysis.

sectors ai search
Enterprise Level AI Search

Query in English or Bahasa Indonesia. Search across all your data.

avatarUse out-of-the-box AI models for our business

Hallucination

avatarBuild RAG (Retrieval-Augmented Generation) modelsSensible
avatarWe could upload all our data to Chat-G-P-Tee

Risky

Incorporate AI Models into your data
With Supertype's experience, you can connect any AI Models of your choice with any data source in a highly secure, fully managable configuration.
avatar

Who can we hire to build out AI tooling that incorporates into our business processes?

Supertype is the trusted AI developer among Indonesia's largest enterprises

Enterprise-ready Chatbots
Powered by the world's most advanced open-source AI models like LLaMa and DeepSeek.

Real-time ETL Pipelines for Fiscal Policymaking

audit board of indonesia bpkThe Audit Board of Indonesia (BPK RI) is a state institution mandated to audit the management of state finances in Indonesia. Supertype works with BPK to augment their BIDICS platform with full-fledged search capabilities, AI content tagging, PDF parsing, and AI-powered analytics.

AI-powered Big Data Platform

  • Large Language Models that powers the text extraction of more than 1,500 PDF documents and audit reports
  • Bespoke AI that automatically tags and categorize audit reports based on their content, metadata and the geographical location concerning the audit
  • A re-engineering of the BIDICS platform to support a much heavier analytics workload, with AI-assisted analytics, AI-powered search, and high performance data retrieval

0
1
2
3
4
5
6
7
8
9
,
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9

Audit Reports PDFs

0
1
2
3
4
5
6
7
8
9
tb

Data processed

PDF to Queryable Databases

Supertype has to process upwards of 450 PDF documents and audit reports (annual, financial, performance, compliance, and special audits), creating AI tools that can extract, tag, and categorize each of these PDF documents into a queryable database. This database is then used to power the BIDICS platform, enabling BPK to search, analyze, and visualize the data contained within these reports.


AI discovers patterns and linkages to business goals

Supplemented with LLM models and AI-powered analytics, each of the aforementioned reports are also mapped to one of UN (United Nations) SDGs (Sustainable Development Goals), of which there are 17 in total. This allows BPK to track the progress of the Indonesian government in achieving these goals, and to provide recommendations on how to improve the country's performance in these areas.


Large Language Models Expertise

The team at Supertype that specializes in LLM are vastly experienced in building custom question-and-answer systems that seamlessly plug into your own data — be it a database, a document archive, or data stored in some proprietary format. We've developed and deployed a number of knowledge retrieval systems that combine the best in production-ready RAGs (Retrieval Augmented Generation) with scalable vector stores trained from your custom data sources, and serve clients from Singapore, Indonesia and Canada in building their own LLM-powered applications.

> 300,000 views from 56+ countries for our LLM course

With more than 300,000 YouTube views and another 150,000 views on licensed platforms, our Large Language Model course is highly popular among AI practitioners. Our course has attracted students from 56 countries, licensed by universities in the region, and used by students and professionals alike.


LLM Education

LLM Development Services

  • Custom AI-powered Search Engines
  • Enterprise Chatbots
  • Domain-trained Expert Systems
  • Conversational Commerce & Interface

Frequently Asked Questions

What do LLM development services include?
LLM development services cover the full lifecycle of building production applications on large language models: use-case scoping, Retrieval-Augmented Generation (RAG), fine-tuning where it adds value, prompt and tool design, evaluation, and the observability and infrastructure needed to run the system reliably at scale. Supertype builds these as production systems, not demos.
What is Retrieval-Augmented Generation (RAG) and do you build RAG systems?
RAG grounds a language model on your own data — documents, databases, or APIs — so it answers from current, authoritative sources instead of its frozen training data. Yes, building production RAG systems is a core part of our LLM work, including the retrieval pipelines, vector stores, and evaluation that keep answers accurate.
Do you fine-tune models or use off-the-shelf LLMs?
Both, depending on the problem. Most enterprise needs are met faster and more cheaply with strong off-the-shelf models plus RAG and good prompting. We recommend fine-tuning only when it demonstrably improves quality, latency, or cost for your specific task, and we measure that with evaluations before committing.
How do you evaluate and monitor LLMs in production?
We build evaluation suites that measure answer quality against your real tasks, and we instrument systems with logging and observability so you can track quality, cost, latency, and failures once they are live. This is the difference between an LLM demo and a system you can trust in production — and it is a theme of our publication, The Enterprise AI Agentic Stack.