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Panofy VS Polygres

Compare Panofy VS Polygres, what is the difference between Panofy and Polygres?

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Summarize

Panofy summarize

Panofy Landing Page

Polygres summarize

Polygres turns Postgres into working memory for AI agents. Retrieve structured rows, connected relationships, semantic matches, and full-text results through one hybrid API. All without a separate vector store, graph database, or sync pipeline. Build grounded agents over the data you already have, with relational, graph, and vector context joined at the source. Use the managed cloud or self-host with our open source components. Polygres is currently free to use, just sign up!

Polygres Landing Page

Compare Details

Panofy details

Categories AI Developer Tools, AI Agent
Panofy Website https://panofy.ai?utm_source=Toolify&utm_medium=referral&utm_campaign=product_launch
Added Time April 14 2026
Panofy Pricing --

Polygres details

Categories AI Developer Tools, AI Agent, AI Knowledge Graph, AI API, AI Search Engine
Polygres Website https://polygres.com?utm_source=toolify
Added Time August 26 2026
Polygres Pricing --

Comparison of usage

How to use Panofy?

Activating an Invite Code After registering on the homepage, you will automatically be added to the invite code waitlist. Check your email for your invite code. Training Your Agent Training is the core step in Panofy. Once training is complete, your agent retains the role definition, task scope, and output requirements you have set, and applies them consistently in every subsequent conversation — no need to re-explain the background each time. 1. In the Agent Workspace, click "+ New Agent" in the top-right corner to begin the creation process. 2. Name your agent based on its intended function — for example, "TweetForge". 3. In the training input field, provide instructions or knowledge content for your agent. Define its role, task scope, output format requirements, and tone preferences. 4. Upload files to accelerate knowledge building. Suitable materials include SOPs, business guidelines, evaluation frameworks, and reference examples. 5. Click "Submit" to begin training. You will be automatically redirected to the Agent Workspace, where training progress updates in real time. 6. Once training is complete, the agent's status changes from "Training" to "Ready". You can then proceed to the next step. Assigning Tasks to Your Agent Once training is complete, your agent has internalized its setup and is ready to receive and execute task instructions. Executing a Task 1. In the Agent Workspace, click on the relevant agent to open the conversation interface. 2. Enter your task instructions in the input box and send. The agent will begin executing the task automatically. 3. Results are displayed in real time in the conversation window and simultaneously saved to the "Output" panel on the left. Creating a New Task 1. Click "New Task" in the right-hand navigation bar to create an additional task for the same agent. 2. For complex tasks, the agent will automatically generate a task plan listing each step. You can then choose to execute immediately, schedule execution, or revise the plan. 3. Once execution is confirmed, you can monitor the progress of each sub-task in real time. 4. Click "Import" in the right-hand navigation bar to bring in an existing task plan from another complex task. This allows established workflows to be saved and reused directly. Inviting Collaborators and Sharing 1. Click "Invite" in the right-hand navigation bar to generate an invite link. Anyone with the link can use your trained agent directly, with any credits consumed charged to their own account. You can configure whether to include access to external tools and whether to require a passcode. 2. Click the share icon above the conversation to generate a shareable link for the task record. You can set visibility to "Anyone with the link" or "Only me", and optionally enable playback mode so external viewers can replay the task without needing to register. You're ready to start. Create your first agent, train it, and let it become a genuine part of how you work. The more you put in, the better it gets.

How to use Polygres?

Create a Polygres managed instance or install the open-source components on an existing PostgreSQL database. Connect your schema and use the SDK or retrieval API to submit a natural-language query with options such as graph traversal depth, filters, and token limits. Polygres combines relational, graph, vector, and text results into one ranked, token-ready context block that can be passed directly to an AI agent.

Compare Pros between Panofy and Polygres

Core features of Panofy

  • - Agent Training — Train a reusable AI agent with a single sentence. No more rewriting context every session. Your agent carries your instructions forward, reducing communication overhead and token consumption.
  • - Long-Term Memory — As your agent works, it automatically learns experience and reflects on mistakes. The more you use it, the better it understands you.
  • - Agent Swarm — Manage an entire team of AI agents from one platform. Each agent maintains its own dedicated knowledge base and memory, ready to handle its specialized role.

Core features of Polygres

  • Unified relational, graph, vector, and full-text retrieval
  • Native graph traversal over existing PostgreSQL foreign keys
  • Fused hybrid search with dense HNSW, sparse, filtered, and semantic retrieval
  • Token-ready context assembly for grounded AI agents
  • Shortest-path, neighborhood, relationship, and multi-hop graph queries
  • Managed cloud hosting and open-source self-hosting
  • PostgreSQL-native data retrieval without a separate vector store or sync pipeline

Compare Use Cases

Use cases for Panofy

  • You can train a content assistant that understands your brand voice and continuously generates on-tone copy and content ideas.
  • You can upload your company's SOPs and product documentation to turn an agent into an onboarding guide for new hires or a customer-facing support bot.
  • You can define a competitive analysis framework and have an agent produce structured reports to that same standard, every time.
  • What these scenarios share is that the agent doesn't just answer once — it becomes a stable, long-term part of how you work.

Use cases for Polygres

  • Build grounded AI agents that retrieve customer records, orders, tickets, and related history
  • Investigate failed transactions by combining semantic search with order, payment, and dispute relationships
  • Create user-memory systems that retrieve relevant past interactions and connected data
  • Query Wikipedia-scale datasets using hybrid indexes and graph relationships
  • Provide support agents with ranked, database-backed context
  • Develop recommendation and discovery systems using existing PostgreSQL data

Different Plan between Panofy and Polygres

Panofy

Free / BASIC

$20 / PLUS

$200 / PRO

Polygres

Self-Hosted

$0 / forever

Open-source pgGraph and pgVector, runnable on any PostgreSQL instance, with community support.

Free Launch

$16 / month

Managed cloud database hosting with email and community Discord support. Currently free for now.

Scale

$256 / month minimum usage

Automated vertical and horizontal scaling, email and community Discord support, private Discord or Slack channel, and support hours from 8:00 AM to 5:00 PM.

Enterprise

$4,096 / month minimum usage

Coming soon. Includes dedicated database infrastructure, custom compliance, high availability, 24/7 support, and dedicated support and uptime SLAs.

Compare Traffic/Monthly Visitors

Panofy's traffic

Panofy is the one with 0 monthly visits and 00:00:00 Avg.visit duration. Panofy has a Page per visit of 0.00 and a bounce rate of 0.00%.

Visit Over Time

Monthly Visits 0
Avg·visit Duration 00:00:00
Page per Visit 0.00
Bounce Rate 0.00%
Jan 2026 - Jul 2026 All traffic:

Polygres's traffic

Polygres is the one with 11.6K monthly visits and 00:00:12 Avg.visit duration. Polygres has a Page per visit of 1.40 and a bounce rate of 92.09%.

Visit Over Time

Monthly Visits 11.6K
Avg·visit Duration 00:00:12
Page per Visit 1.40
Bounce Rate 92.09%
May 2026 - Jul 2026 All traffic:

Geography

Sorry, there are no data

Geography

The top 1 countries/regions for Polygres are:United States 100.00%

Top 1 Countries/regions

United States
100.00%

Traffic Sources

The 6 main sources of traffic to Panofy are:Mail 0, vs_sourcesGenAi 0, Direct 0, vs_sourcesAffiliate 0, Referrals 0, vs_sourcesDisplayAds 0, vs_sourcesSearchPaid 0, vs_sourcesSocialPaid 0, vs_sourcesSearchOrganic 0, vs_sourcesSocialOrganic 0

Mail
0
vs_sourcesGenAi
0
Direct
0
vs_sourcesAffiliate
0
Referrals
0
vs_sourcesDisplayAds
0
vs_sourcesSearchPaid
0
vs_sourcesSocialPaid
0
vs_sourcesSearchOrganic
0
vs_sourcesSocialOrganic
0
Jan 2026 - Jul 2026 Worldwide Desktop Only

Traffic Sources

The 6 main sources of traffic to Polygres are:Direct 57.14%, vs_sourcesSocialOrganic 21.37%, vs_sourcesSearchOrganic 13.47%, Referrals 5.27%, Mail 2.75%, vs_sourcesGenAi 0.00%, vs_sourcesAffiliate 0.00%, vs_sourcesDisplayAds 0.00%, vs_sourcesSearchPaid 0.00%, vs_sourcesSocialPaid 0.00%

Direct
57.14%
vs_sourcesSocialOrganic
21.37%
vs_sourcesSearchOrganic
13.47%
Referrals
5.27%
Mail
2.75%
vs_sourcesGenAi
0.00%
vs_sourcesAffiliate
0.00%
vs_sourcesDisplayAds
0.00%
vs_sourcesSearchPaid
0.00%
vs_sourcesSocialPaid
0.00%
May 2026 - Jul 2026 Worldwide Desktop Only

Which is better: Panofy or Polygres?

Polygres might be a bit more popular than Panofy.As you can see, Panofy has 0 monthly visits, while Polygres has 11.6K monthly visits. So more people choose Polygres. So the odds are that people will recommend Polygres more on social platforms.

Panofy has an Avg.visit duration of 00:00:00, while Polygres has an Avg.visit duration of 00:00:12. Also, Panofy has a page per visit of 0.00 and a Bounce Rate of 0.00%. Polygres has a page per visit of 1.40 and a Bounce Rate of 92.09%.

The main users of Polygres are United States, with the following distribution: 100.00%.

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