All analysis was generated autonomously, without human review. Scores are analytical opinions drawn from the cited public sources, without hands-on testing. They are not audits, certifications, investment reports, purchasing advice, or evaluations of quality.
Hirundo edits the weights of an already-trained AI model so it forgets specific things it learned, jailbreak weaknesses, memorized personal data, hallucination triggers, and bias, instead of retraining it. A Google DeepMind-hosted case study reports Hirundo's own result: hardening a Gemma model cut successful attacks by about three-quarters while keeping its benchmark scores. That result also names the threat, because the model providers Hirundo hardens could fold unlearning into their own training. Founders from the Technion give the team real academic standing, and Hirundo is an early entrant in a young discipline. It has no named paying customer and no proprietary dataset in the public record, so today the lead is being first, not being hard to copy.
| Description | Hirundo builds a machine unlearning platform that removes memorized PII, jailbreak vulnerabilities, biases, and hallucination-causing data from already-trained AI models without full retraining. | [f1] |
|---|---|---|
| Founded | 2023 | [f2] |
| HQ | Tel Aviv, Israel | [f2] |
| Funding | $8M total | [f3] |
| Latest funding | Seed ($8M, June 2025, led by Maverick Ventures Israel) | [f2] |
| Product | What it does |
|---|---|
| Hirundo Machine Unlearning Platform | Detects weaknesses in trained models, then surgically removes the parameters behind unwanted behavior such as jailbreaks, hallucinations, bias, and memorized data, without full retraining. |
AI Defense Matrix
| Govern | Identify | Protect | Detect | Respond | Recover | |
|---|---|---|---|---|---|---|
| AI-Workload Platforms Inference servers, training platforms, vector DB platforms, and the model-loading supply chain. | ||||||
| AI Orchestration Tools Agentic orchestration tools, plus their plugins, skills, hooks, system prompts, scaffolding, harnesses, configuration settings, and MCP clients on user devices. | ||||||
| AI-Generated Code Code produced by AI tools, AI-assisted reviews, AI-generated infrastructure-as-code and tests, and vibe-coded apps that bypass CI/CD. | ||||||
| AI Gateways & Routers MCP proxies and gateways, LLM routers, outbound AI-service traffic, shadow AI egress, and model-registry traffic. | ||||||
| AI Model Model weights, fine-tuning checkpoints, model cards, registries, AIBOM, and the third-party LLMs your enterprise consumes. | ||||||
| Training Data Datasets used for training, fine-tuning, and continued learning. | ||||||
| Runtime AI Data User prompts, inference inputs, RAG content, vector DB content, persistent agent memory, and interaction history. | ||||||
| AI Agent Identities AI agents as non-human principals, plus credentials, keys, permission scopes, service accounts, and delegation chains across agents and tools. |
The Hirundo Machine Unlearning Platform removes the parameters behind jailbreaks, bias, hallucinations, and memorized data in trained models, and screens training data for the issues that cause them. These capabilities are mapped to the AI Defense Matrix. [f4]
How well the company can compete in its security market, scored across eight dimensions against public evidence.
| Dimension | Score |
|---|---|
| Problem Clarity How precisely the company defines its problem, with evidence the problem exists at the scale claimed. | 3/5 |
| Capability Depth How specific the technical capabilities are, with evidence beyond marketing claims such as docs, demos, and third-party validation. | 4/5 |
| Market Timing Whether the market is ready for this product, with evidence that buyers are actively seeking solutions. | 3/5 |
| Team Credibility Demonstrated domain expertise with public signals such as prior exits, publications, and industry recognition. | 3/5 |
| GTM Proof Evidence of actual traction (customers, revenue signals, partnerships) beyond stated intentions. | 2/5 |
| Funding Efficiency Whether funding matches go-to-market ambition, with signs of capital-efficient growth. | 3/5 |
| Category Clarity Whether the company creates or fits a recognizable category that buyers can quickly place in their stack. | 3/5 |
| Incumbent Defensibility How vulnerable the core value proposition is to absorption as a feature by a platform vendor. | 3/5 |
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A closer look at the company's product strategy, measuring how defensible it is against market forces and examining the eight areas behind it.
pivot urgently
| Dimension | Score |
|---|---|
| Value Delivery Does the product sell software as the product, or judgment, trust, or accountability with software as the delivery mechanism. | 1/3 |
| Switching Cost How expensive leaving is for a customer: data portability, integrations, learned workflows, network effects, regulatory data residency. | 2/3 |
| Compliance Moat Whether certifications, liability acceptance, or audit trails block an easy replacement. | 1/3 |
| Problem Complexity Whether the product requires ML, optimization, real-time systems, or years of specialized expertise. | 3/3 |
| Buyer Profile Whether buyers are SMB operators, mid-market IT teams, or regulated enterprises and governments with procurement gates. | 2/3 |
| Layer Whether the product is an end-user application, a platform with application features, or infrastructure other applications depend on. | 2/3 |
| Proprietary Data, Content, or IP Whether the product accumulates datasets, content licenses, or IP that a rival cannot recreate from scratch. | 1/3 |
Unlock the Full Analysis
The reasoning for the scores, the strategy deep dive, the business risks, and more. AI access comes with the purchase, so your AI tools can read the full profile too. You keep 12 months of access.
One-time purchase: $20 per profile.
UnlockReading several? Unlock the entire catalog.
| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | https://www.hirundo.io/ | official | 2026-06-25 |
| f2 | PR Newswire: Hirundo Raises $8M Seed to Make AI Forget Hallucinations, Biases and Vulnerabilities | press | 2026-06-25 |
| f3 | SecurityWeek: Hirundo Raises $8 Million to Eliminate AI's Bad Behavior | press | 2026-06-25 |
| f4 | AI Defense Matrix Catalog: Hirundo | official | 2026-06-25 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | Hirundo homepage: Machine Unlearning Platform “Machine Unlearning surgically removes risky knowledge and behavior from trained LLMs at the model level, without retraining.” | official | 2026-06-25 |
| s2 | Hirundo about page (founders and roles) “Ben Luria CEO and Co-Founder Rhodes Scholar. Michael Leybovich CTO and Co-Founder Previously a graduate CS researcher at the Technion. Prof. (Emeritus) Oded Shmueli Chief Scientist and Co-Founder Previously the Dean of Computer Science and Executive VP at the Technion.” | official | 2026-06-25 |
| s3 | Hirundo for AI teams: Detect and fix risks in your AI models (model coverage FAQ) “Open-weight models (both OSS base models and fine-tuned variants), where we directly edit the model's weights. Closed-weight/API models (like Gemini or ChatGPT), where we use a separate mechanism called Prism relying on log probs to change model behavior at inference time.” | official | 2026-06-25 |
| s4 | Hirundo Data QA page (SOC 2 self-claim, SaaS / VPC / air-gapped deployment) “Our SOC-2 certified solution runs as an API or platform, with deployment available via SaaS, VPC, or air-gapped on-premises.” | official | 2026-06-25 |
| s5 | Google DeepMind Gemmaverse case study on Hirundo (weight-level hardening of Gemma 4 E4B, attack-success-rate results) “Hirundo's weight-optimization process achieved a 74.47% reduction in successful attacks relative to the base model, resulting in a final Attack Success Rate (ASR) of 4.78%.” | research | 2026-06-25 |
| s6 | PR Newswire: Hirundo Raises $8M Seed (founders, round, sector applications) “Hirundo - specialists in machine unlearning, has raised an $8M seed funding round, led by Maverick Ventures Israel, with participation from SuperSeed, Alpha Intelligence Capital, Tachles VC, AI.FUND and Plug and Play Tech Center.” | press | 2026-06-25 |
| s7 | SecurityWeek: Hirundo Raises $8 Million to Eliminate AI's Bad Behavior “The product supports both generative and non-generative systems and is used by organizations across the finance, government, healthcare, and other sectors.” | press | 2026-06-25 |
| s8 | SiliconANGLE: Hirundo raises $8M to make AI forget bad data (model coverage, gated-model roadmap) “it can do this for both open-source models such as Llama and Mistral, and soon it will also be able to do the same for gated models such as OpenAI's GPT and Anthropic PBC's Claude.” | press | 2026-06-25 |
| s9 | Calcalist: Hirundo raises $8M in Seed funding to help AI forget its mistakes “The round was led by Maverick Ventures Israel, with participation from SuperSeed, Alpha Intelligence Capital, Tachles VC, AI.FUND, and Plug and Play Tech Center.” | press | 2026-06-25 |
| s10 | AI Defense Matrix Catalog: Hirundo (AI Model primary, Training Data secondary) “Machine unlearning that removes memorized PII, jailbreak vulnerabilities, and biased behaviors from trained models without retraining.” | official | 2026-06-25 |
| s11 | Hirundo Data QA page, SOC 2 self-claimed, no inspectable trust center (/trust and /security return 404, trust. and security. subdomains do not resolve) “Our SOC-2 certified solution runs as an API or platform, with deployment available via SaaS, VPC, or air-gapped on-premises.” | official | 2026-06-25 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | Hirundo homepage: Machine Unlearning Platform “Machine Unlearning surgically removes risky knowledge and behavior from trained LLMs at the model level, without retraining.” | official | 2026-06-25 |
| s2 | Hirundo about page (founders and roles) “Ben Luria CEO and Co-Founder Rhodes Scholar. Michael Leybovich CTO and Co-Founder Previously a graduate CS researcher at the Technion. Prof. (Emeritus) Oded Shmueli Chief Scientist and Co-Founder Previously the Dean of Computer Science and Executive VP at the Technion.” | official | 2026-06-25 |
| s3 | Hirundo for AI teams: Detect and fix risks in your AI models (model coverage FAQ) “Open-weight models (both OSS base models and fine-tuned variants), where we directly edit the model's weights. Closed-weight/API models (like Gemini or ChatGPT), where we use a separate mechanism called Prism relying on log probs to change model behavior at inference time.” | official | 2026-06-25 |
| s4 | Hirundo Data QA page (SOC 2 self-claim, SaaS / VPC / air-gapped deployment) “Our SOC-2 certified solution runs as an API or platform, with deployment available via SaaS, VPC, or air-gapped on-premises.” | official | 2026-06-25 |
| s5 | Google DeepMind Gemmaverse case study on Hirundo (weight-level hardening of Gemma 4 E4B, attack-success-rate results) “Hirundo's weight-optimization process achieved a 74.47% reduction in successful attacks relative to the base model, resulting in a final Attack Success Rate (ASR) of 4.78%. Crucially, this hardening strictly preserved the model's high performance across standard utility benchmarks.” | research | 2026-06-25 |
| s6 | PR Newswire: Hirundo Raises $8M Seed (founders, round, metrics, sector applications) “When deployed, Hirundo's solution has led to the removal of up to 70% of biases - as demonstrated in their work on DeepSeek-R1, as well as up to 55% reduction of hallucinations and 85% decrease in successful prompt injections, showcased with the company's work on Llama.” | press | 2026-06-25 |
| s7 | SecurityWeek: Hirundo Raises $8 Million to Eliminate AI's Bad Behavior “The product supports both generative and non-generative systems and is used by organizations across the finance, government, healthcare, and other sectors.” | press | 2026-06-25 |
| s8 | SiliconANGLE: Hirundo raises $8M to make AI forget bad data (model coverage, gated-model roadmap) “it can do this for both open-source models such as Llama and Mistral, and soon it will also be able to do the same for gated models such as OpenAI's GPT and Anthropic PBC's Claude.” | press | 2026-06-25 |
| s9 | Calcalist: Hirundo raises $8M in Seed funding (round, investors, founded 2023) “The round was led by Maverick Ventures Israel, with participation from SuperSeed, Alpha Intelligence Capital, Tachles VC, AI.FUND, and Plug and Play Tech Center. Founded in 2023, Hirundo is pioneering a discipline known as machine unlearning.” | press | 2026-06-25 |
| s10 | AI Defense Matrix Catalog: Hirundo (AI Model primary, Training Data secondary) “Machine unlearning that removes memorized PII, jailbreak vulnerabilities, and biased behaviors from trained models without retraining.” | official | 2026-06-25 |
| s11 | Hirundo Data QA page, SOC 2 self-claimed, no inspectable trust center (/trust and /security return 404, trust. and security. subdomains do not resolve) “Our SOC-2 certified solution runs as an API or platform, with deployment available via SaaS, VPC, or air-gapped on-premises.” | official | 2026-06-25 |
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