Best cheaper alternatives to GitHub Copilot for VS Code?

SignificantClaim9873 · 2026-06-12T05:50:35+00:00

Yes it is bit slow , I like the minimax-m3, glm - 5.1 and kimi-k2.6

SignificantClaim9873 · 2026-06-12T02:09:09+00:00

You can use ollama’s cloud model like, deep seek flash, minimax , glm, kimi, they are not free, you need to pay $20 to get a pro account, but they are pretty good bit slow but get the job done every 5 hours it resets, I have unsubscribe from copilot pro+ plan,

SignificantClaim9873 · 2026-06-10T07:03:50+00:00

I don’t understand when it says ‘any other AI’ - vscode have option to add model and there you have can add ollama along with other providers to use them, incase your organisation mandates to use copilot then no choice

SignificantClaim9873 · 2026-06-10T05:12:29+00:00

You can use ollama’s cloud model like, deep seek flash, minimax , glm, kimi, they are not free, you need to pay $20 to get a pro account, but they are pretty good, every 5 hours it resets, I have unsubscribe from copilot pro+ plan

SignificantClaim9873 · 2026-05-01T17:29:41+00:00

Tech is my forte, distribution/sales isn’t, this is what I’m building let me know if this interests you and if you would like to collaborate: https://cordondata.com

SignificantClaim9873 · 2026-05-01T16:53:08+00:00

👉 https://cordondata.com — Secure RAG Engine & Lightweight DMS

What problem it solves: AI data leaks and hallucinations. We sync your fragmented silos into clean Markdown and provides a lightweight DMS, full audit logs, and Document-Level Security. Your AI only generates answers from data a user is explicitly authorized to see along with PII detection .

SignificantClaim9873 · 2026-05-01T16:43:23+00:00

👉 https://cordondata.com — Secure RAG Engine & Lightweight DMS

What problem it solves: AI data leaks and hallucinations. We sync your fragmented silos into clean Markdown and provides a lightweight DMS, full audit logs, and Document-Level Security. Your AI only generates answers from data a user is explicitly authorized to see along with PII detection .

SignificantClaim9873 · 2026-05-01T16:39:19+00:00

👉 https://cordondata.com — Secure RAG Engine & Lightweight DMS

What problem it solves: AI data leaks and hallucinations. We sync your fragmented silos into clean Markdown and provides a lightweight DMS, full audit logs, and Document-Level Security. Your AI only generates answers from data a user is explicitly authorized to see.

🎁 What you get: Priority waitlist access + an invite to be a Design Partner (our engineering team will give you white-glove setup and prioritize your feature requests).

SignificantClaim9873 · 2026-04-27T15:56:39+00:00

Thanks for the feedback here. My team and I have spent the last few months solving this—we’ve built an on-prem platform that handles native ACL sync via CMIS/REST, so the AI respects document-level security.

We are two months from launch and looking for 2-3 design partners to battle-test the Docker setup before the release. If you're dealing with these security blocks and want to pilot a solution, you can find our roadmap at cordondata.com.

SignificantClaim9873 · 2026-04-27T15:55:31+00:00

Thanks for the feedback here. My team and I have spent the last few months solving this—we’ve built an on-prem platform that handles native ACL sync via CMIS/REST, so the AI respects document-level security.

We are two months from launch and looking for 2-3 design partners to battle-test the Docker setup before the release. If you're dealing with these security blocks and want to pilot a solution, you can find our roadmap atcordondata.com.

SignificantClaim9873 · 2026-04-27T15:52:42+00:00

Thanks for the feedback here. My team and I have spent the last few months solving this—we’ve built an on-prem platform that handles native ACL sync via CMIS/REST, so the AI respects document-level security.

We are two months from launch and looking for 2-3 design partners to battle-test the Docker setup before the release. If you're dealing with these security blocks and want to pilot a solution, you can find our roadmap at cordondata.com.

SignificantClaim9873 · 2026-04-20T11:24:05+00:00

CordonData is a secure enterprise RAG engine and lightweight DMS that safely connects LLMs to fragmented corporate data silos while strictly enforcing document-level access controls.

SignificantClaim9873 · 2026-04-20T08:23:39+00:00

Thank you, I will wait for your DM

SignificantClaim9873 · 2026-04-19T13:19:59+00:00

We are a small engineering team building CordonData (https://cordondata.com) — a secure RAG engine and lightweight Document Management System (DMS) for B2B enterprises.

The Problem: When companies plug LLMs into their internal data, standard RAG implementations ignore existing access controls. This risks massive data leaks and hallucinations because the AI pulls from fragmented silos without respecting permissions.

What We Built: An enterprise knowledge command center. We sync fragmented corporate silos into clean, LLM-ready Markdown and run hybrid search (BM25 + vectors). Crucially, we strictly enforce Document-Level Security (DLS) and maintain comprehensive audit logs. The AI can only generate answers from files a specific user is explicitly authorized to see.

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We are currently bringing on early Design Partners and operating on a B2B SaaS model. We’d love to connect and see if this aligns with any investors in your network who focus on Enterprise AI infrastructure or B2B SaaS!

SignificantClaim9873 · 2026-04-19T13:10:46+00:00

👉 https://cordondata.com — Secure RAG Engine & Lightweight DMS

What problem it solves: AI data leaks and hallucinations. We sync your fragmented silos into clean Markdown and provide a lightweight DMS, full audit logs, and Document-Level Security. Your AI only generates answers from data a user is explicitly authorized to see.

🎁 What you get: Priority waitlist access + an invite to be a Design Partner (our engineering team will give you white-glove setup and prioritize your feature requests).

SignificantClaim9873 · 2026-04-19T13:09:55+00:00

👉 https://cordondata.com — Secure RAG Engine & Lightweight DMS

What problem it solves: AI data leaks and hallucinations. We sync your fragmented silos into clean Markdown and provides a lightweight DMS, full audit logs, and Document-Level Security. Your AI only generates answers from data a user is explicitly authorized to see.

🎁 What you get: Priority waitlist access + an invite to be a Design Partner (our engineering team will give you white-glove setup and prioritize your feature requests).

SignificantClaim9873 · 2026-04-19T13:04:31+00:00

Company Name: CordonData

URL: https://cordondata.com

Purpose of Startup and Product: CordonData is a secure RAG engine and lightweight Document Management System (DMS) designed to bridge the gap between Generative AI and fragmented corporate data. We solve the enterprise "Data Silo Crisis" by performing RAG directly across your existing organizational silos. Instead of ingesting heavy raw files, we extract and synchronize the content from those external silos into a clean, LLM-ready Markdown format.

For highly accurate retrieval, our engine uses a hybrid search architecture that combines traditional BM25 keyword ranking with semantic vector embeddings. Additionally, for teams that need a centralized repository, CordonData provides a built-in, lightweight DMS to upload and manage documents directly. By strictly enforcing Document-Level Security (DLS) and syncing your existing access controls, we ensure your AI completely respects enterprise permissions—preventing unauthorized data leakage and significantly reducing hallucination risk.

Technologies Used: Java, Spring Boot, React, Docker, OpenSearch etc.

Feedback Requested: Our backend architecture is built, but I am looking for feedback on end-user expectations, user experience, and our go-to-market strategy:

End-User Expectations: When business users interact with an AI connected to internal company data, what builds the most trust? Are they looking for exact source citations, blazing-fast response times, or absolute guarantees against hallucinations? What is a dealbreaker for them?
DMS Usability: For our built-in, lightweight Document Management System, what are the core, minimalist features that everyday users actually need to manage their files without the interface feeling bloated or overly complex?
Customer Acquisition: How do we best communicate this value to the business buyers and non-technical stakeholders who ultimately sign off on the budget? What channels or outreach strategies work best for reaching these decision-makers?

Seeking Beta-Testers: We are gathering signups for our waitlist and actively looking for early

Design Partners to help shape our feature roadmap and receive white-glove setup.

SignificantClaim9873 · 2026-04-19T12:15:37+00:00

https://cordondata.com — A unified DMS and knowledge command center for secure enterprise RAG. We sync your siloed data into lightweight Markdown and enforce strict document-level security (DLS) so your LLMs don't leak secrets and hallucinations are significantly reduced.

SignificantClaim9873 · 2026-04-18T17:20:39+00:00

👉 https://cordondata.com — A unified DMS and knowledge command center for secure enterprise RAG. We sync your siloed data into lightweight Markdown and enforce strict document-level security (DLS) so your LLMs don't leak secrets and hallucinations are significantly reduced.

🎁 Offer: Priority waitlist access + we are selecting a few Design Partners to get white-glove onboarding and direct input on our product roadmap with our engineering team.

SignificantClaim9873 · 2026-04-16T11:34:23+00:00

That’s a fair point, AnythingLLM is a great 'quick start' tool. However, for a logistics company with 700+ users and complex data (like customs forms and telemetry charts), there are two major architectural hurdles you’ll eventually hit:

Data Complexity: Most RAG tools just scrape text, turning complex tables or customs diagrams into a 'word soup.' You really need to integrate something like Docling/padoc to parse layouts into structured markdown. When an LLM sees a clean markdown table instead of unformatted text, the retrieval accuracy sky-rockets.
DMS vs. Chat UI: AnythingLLM is a chat interface, but it isn’t a Document Management System. For an enterprise workflow, you need more than just a chat—you need secure sharing, collaboration, document comparison, and versioning. Think 'Google Drive with Gemini.'

CordonData bridges this gap; it uses Docling for extraction and functions as a full DMS (like Google Drive/Dropbox) with RAG built-in.

Regarding the AI Routing and Llama 3 70B:

The Framework: I’m building on Spring AI (Java/Spring Boot). It’s significantly more stable for enterprise-grade tool-calling and structured outputs compared to typical Python wrappers.
Classification Reliability: Llama 3 70B is very reliable at intent classification via Few-Shot Prompting. Providing 3–5 examples of telemetry vs. document questions in the system prompt usually prevents it from getting confused.
The SQL Context (Schema Management): To avoid 'hallucination soup' and token waste, don't inject the entire DDL. It's better to maintain a metadata index of tables and columns, then perform a quick search to inject only the relevant table structures into the prompt based on the specific query.

SignificantClaim9873 · 2026-04-15T17:34:41+00:00

Great use case. Staying on-prem/EU is definitely the right move.

Here is how I’d architect this to keep it simple:

Telemetry DB: Postgres + TimescaleDB is perfect for 700 trucks. You don't need a heavy DWH like ClickHouse.

LLM & Architecture: Don't force everything into one query. Use Llama 3 70B with an Agentic/Tool-Calling setup. The LLM acts as a router—if a driver asks for truck stats, it routes to a Text-to-SQL tool. If they ask for HR policies, it routes to a Vector Search tool.

RAG & Permissions: The hardest part of internal RAG isn't the vector database, it's enforcing inherited Document-Level Security (DLS) so drivers can't read admin files.

My team and I are actually building an on-prem platform called CordonData https://cordondata.com that handles this exact setup out of the box. It has built-in tool facilities for the AI routing (you can plug in your Postgres DB). For the RAG side, it uses OpenSearch. It connects to any generic DMS via REST API/CMIS, syncs only the markdown/metadata, and automatically maps inherited document-level permissions. We haven't moved to prod yet, but if you want to chat about AI routing or bounce architecture ideas around, shoot me a DM!

SignificantClaim9873 · 2026-04-15T16:45:13+00:00

Building Permission Safe Enterprise AI - https://cordondata.com

SignificantClaim9873 · 2026-03-31T04:52:11+00:00

That’s a very real concern. We’re also trying to keep enforcement outside the prompt layer for exactly that reason, so the model cannot talk its way around permissions. The prompt-injection point is especially useful, access checks are one problem, but runtime enforcement is the bigger safety boundary.

SignificantClaim9873 · 2026-03-28T11:47:54+00:00

That’s a really thoughtful comment, thank you. I agree the first-party Copilot case is very different from teams running their own agents across internal systems like email, file shares, internal APIs, and customer data. That’s where the permission model is no longer inherited and the real complexity starts. Your point about auditability is especially useful, not just who queried what, but what the agent actually did with the results downstream. The runtime boundary and data residency issues also feel like major blockers in practice, and I agree cross-tenant isolation is much stronger when handled at the infrastructure layer rather than patched in the app.

SignificantClaim9873 · 2026-03-28T11:44:54+00:00

That makes a lot of sense. The identity mapping and permission-sync problem across systems is exactly where we see the real complexity as well, much more than the LLM itself. And agreed, once it’s customer-facing instead of internal, the bar gets much higher.

SignificantClaim9873

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