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Knowally VS Agentmemory

Compare Knowally VS Agentmemory and see what are their differences

Knowally

Upload your security docs once. Knowally auto-drafts answers to every question in your next security questionnaire — each answer cited from your own documents. Done in hours, not days.

Rating
0 reviews
Pricing
Paid Free trial $99 / Monthly (Starter, 3 users, 50 documents)
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Agentmemory

Persistent memory for Claude Code, Codex & coding agents

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Rating
0 reviews
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Sugarbug
Connect your tools into a living knowledge graph. Sugarbug captures every signal to deliver compounding insights and unified context. sponsored

Which is more popular?

Document Management popularity
100% vs 0%
alternatives listed
36 vs 55

Base details

Website, pricing, platforms and company facts side by side.

Knowally
Agentmemory
Website knowally.com agent-memory.dev
Pricing
Paid Free trial $99 / Monthly (Starter, 3 users, 50 documents) Official pricing
—
Platforms
Web
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Company Startup from Bosnia & Herzegovina · 1 - 9 employees · 2026 —
Listed in
Compliance Management Risk Management Document Management Governance, Risk And Compliance Compliance AI +3
AI Developer Tools Productivity Utilities +1

About Knowally and Agentmemory

In their own words, as submitted to SaaSHub.

Knowally
Agentmemory

Knowally automates security questionnaire responses for software vendors and InfoSec teams. Upload your SOC 2 reports, ISO 27001 controls, and security policies once — Knowally's AI uses them to auto-fill incoming CAIQ, SIG, DDQ, VSA, and custom questionnaires in minutes instead of days....

Read more about Knowally

No description of Agentmemory yet.

Features and specs

What each product offers, as listed by its team.

Knowally 8 features
Agentmemory 5 features
  • AI-powered answering
    Automatically drafts answers from your document library using Claude AI
  • Confidence scoring
    Each answer is rated HIGH / MEDIUM / LOW confidence with a source citation
  • Document library
    Upload and manage security documents (SOC 2, ISO 27001, policies)
  • Questionnaire import
    Upload vendor questionnaires in Excel or CSV format
  • CSV export
    Export completed questionnaires for direct submission
  • Answer reuse
    Answered questions are saved to a library and reused across future questionnaires
  • Multi-User Workspaces
    Team members collaborate within a shared tenant workspace
  • Audit log
    Full activity history for compliance and traceability
  • Simple API
    Agentmemory provides a straightforward and minimal API for creating, searching, updating, and deleting memories, making it easy for developers to integrate memory capabilities into AI agents without dealing with complex configurations.
  • Built on ChromaDB
    It leverages ChromaDB as its underlying vector database, providing reliable semantic search and embedding capabilities out of the box without requiring developers to set up separate infrastructure.
  • Lightweight and Easy to Install
    Agentmemory is a lightweight Python package that can be installed via pip with minimal dependencies, making it quick to get started with and easy to incorporate into existing projects.
  • Category-Based Memory Organization
    Memories can be organized into categories (topics), allowing agents to store and retrieve information in a structured way, which helps with context management and retrieval accuracy.
  • No Server Required
    Agentmemory can run entirely locally without needing a separate server or cloud service, making it suitable for development, prototyping, and privacy-sensitive applications where data should stay on the local machine.

Possible disadvantages

  • Limited Ecosystem and Community
    Agentmemory is a relatively niche and small project with a limited community compared to more established memory and vector database solutions, which means fewer resources, tutorials, and community support are available.
  • Basic Feature Set
    While simplicity is a strength, the library may lack advanced features such as sophisticated memory consolidation, decay mechanisms, importance scoring, or complex querying capabilities that more mature memory frameworks offer.
  • Tight Coupling to ChromaDB
    Being built specifically on ChromaDB means developers are locked into that particular vector store and cannot easily swap it out for alternatives like Pinecone, Weaviate, or FAISS without significant refactoring.
  • Limited Scalability
    As a locally-run, lightweight solution, Agentmemory may not scale well for production applications that require handling large volumes of memories, high concurrency, or distributed deployments.
  • Sparse Documentation and Examples
    The project's documentation, while covering the basics, may lack comprehensive examples, best practices, and advanced usage patterns that developers need when building complex agent-based systems.

Analysis

An editorial look at what each product does well and who it suits.

Knowally
Agentmemory

Overall verdict

  • I don't have verified, up-to-date information about knowally.com specifically, so I can't confirm its quality, legitimacy, or user satisfaction with certainty. Before using it, I'd recommend checking independent reviews, verifying company details, and testing any free tier or trial to assess real-world performance.

Why this product is good

  • No verified independent reviews or reliable data source was available to confirm claims made by the service
  • Unable to confirm business legitimacy, security practices, or customer support quality without direct verification
  • Cannot validate pricing fairness or feature accuracy compared to competitors without current data

Recommended for

  • Users willing to do their own due diligence, such as checking Trustpilot, Reddit, or BBB reviews before committing
  • Those comfortable testing a free trial or demo before making a purchase decision
  • Anyone who wants to verify company registration, contact info, and refund policies directly on the site

Overall verdict

  • AgentMemory (agent-memory.dev) appears to be a solid, purpose-built solution for developers who need persistent memory management in AI agent applications, offering a focused feature set for storing, retrieving, and managing contextual data across agent sessions.

Why this product is good

  • Provides dedicated memory persistence for AI agents, enabling context retention across sessions and conversations
  • Designed specifically for the agentic AI use case, which can simplify development compared to building custom memory layers
  • Likely offers developer-friendly APIs and SDKs to integrate memory capabilities quickly
  • Can improve agent performance by allowing recall of past interactions, user preferences, and long-term context
  • Reduces boilerplate work for teams building conversational or autonomous AI systems

Recommended for

  • Developers building AI agents or LLM-powered applications that require long-term memory
  • Teams creating conversational assistants that need to remember user context across sessions
  • Startups and companies prototyping autonomous or multi-step agent workflows
  • Engineers seeking a managed memory layer instead of building persistence infrastructure from scratch
  • Projects involving personalized AI experiences that depend on retained user data and history

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Knowally
Agentmemory
100% 100%
Document Management
0% 0%
30% 30%
AI
70% 70%
0% 0%
Developer Tools
100% 100%
100% 100%
Proposals
0% 0%

Questions & Answers

As answered by people managing Knowally and Agentmemory.

What makes your product unique?

Knowally's answer

Most questionnaire tools are built for generic RFP responses. Knowally is purpose-built for security questionnaire automation — it uses your own uploaded security documentation (SOC 2 reports, ISO 27001 controls, internal policies) as the source of truth for every answer. Responses are grounded in your actual documents, not a generic knowledge base, making them accurate and audit-ready from day one.

Why should a person choose your product over its competitors?

Knowally's answer

Knowally is significantly more affordable than Loopio or Responsive with no per-questionnaire fees. It's GDPR-compliant and EU-hosted — critical for European vendors. Setup takes minutes: upload your existing docs and start answering immediately, no onboarding call or training required. The Answer Library compounds over time — each questionnaire you complete makes the next one faster.

How would you describe the primary audience of your product?

Knowally's answer

InfoSec managers, GRC analysts, and trust & compliance teams at B2B SaaS companies and software vendors that receive security questionnaires (CAIQ, SIG, SOC 2, DDQ, VSA) from enterprise customers or investors as part of their sales cycle. Typically 5–500 person companies without a dedicated RFP team.

What's the story behind your product?

Knowally's answer

Knowally was built after experiencing firsthand how much time InfoSec and sales teams waste manually answering the same security questions for every new enterprise customer — copying from old spreadsheets, hunting through policy docs, starting from scratch each time. The goal: upload your security documentation once, let AI handle the repetitive drafting.

Which are the primary technologies used for building your product?

Knowally's answer

Python (Flask) backend, Vue 3 frontend, PostgreSQL with pgvector for semantic search, Anthropic for AI answer generation. Hosted on Hetzner in the EU. GDPR-compliant architecture with all data processing confined to EU regions.

User comments

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