Skild Brain
Real-time simultaneous inference + data collection — dynamically updates in-context representation as the robot encounters new situations. Lets the system adapt to novel embodiments / unseen environments without explicit fine-tuning. Pre-trained on internet human video + physics sim.
Active · Verified 2026-10-22 · fresh as of 2026-10-22 · 30 cited facts, 5 with a third-party source · 1 recorded change · Suggest a correction
At a glance
- Tier
- T1
- Created
- 2023 (Skild AI founded 2023 by Deepak Pathak and Abhinav Gupta; Pittsburgh PA) third-party fix
- Latest release
- not applicable — not OSS fix
- License
- not applicable — not OSS fix
- GitHub
- not applicable — no GitHub repo fix
- Pricing
- No public pricing; $4k–$15k target hardware cost enabled by Skild Brain third-party fix
- Funding
- latest: $1.4B Series C at ›$14B valuation (SoftBank lead, 2026-01); prior $300M Series A (2024-07) vendor fix
- Freshness
- 2026-10-22 fix
- Layer
- agent-infra repo fix
- Licensing
- commercial third-party fix
Memory taxonomy
- storage
- vector
- retrieval
- attention
- persistence
- session
- update
- overwrite
- unit
- episode
- governance
- opaque
- conflict
- overwrite
When to use
Optimised for: real-time perception + spatial reasoning + multi-modal sensor fusion
Anti-fit: not for non-embodied / non-physical use cases
Pros & cons
Pros
Real-time in-context adaptation — robot updates representation as it acts, instead of relying on offline fine-tuning between deployments.
Cons
Robot-specific; rapid in-context updates raise stability concerns under distribution shift; no published failure-mode analysis.
Claims & capabilities
~$30M ARR within months of 2025 commercial launch. $1.4B raised at >$14B (Jan 2026).
Technical surface
- API surface
- searched not found
- Backend storage
- searched not found
- Deployment
- Cloud inference + on-robot edge deployment
- Embedding model
- searched not found
- Multi-tenancy
- searched not found
- MCP
- no MCP support advertised — vertical product, no MCP server / client integration documented
- A2A
- no A2A protocol support advertised — vertical product, no A2A integration documented
- OpenTelemetry
- no OpenTelemetry integration advertised — vendor logs/observability not publicly documented
Alternatives to Skild Brain → live options ranked by shared design, licence, hosting and MCP support
Similar systems
Other vertical / domain-specific ai memory in the catalog, ranked by inbound references.
- Inworld AI T1
Formerly an NPC character engine with named Long-Term Memory; now sells realtime voice models (TTS-2, STT-1, speech-to-speech) and OpenAI-compatible open-model inference. Character/NPC memory is no longer the headline product.
- NVIDIA ReMEmbR T3
Builds long-horizon memory by captioning video segments with VILA, storing captions with timestamps + 3D position coordinates in MilvusDB. At query time, LLM iterates retrieval across text, time, and position modalities. Deployed on Nova Carter robot (Jetson Orin).
- Abridge T1
Clinician-assist ambient documentation. Source mapping: every AI-generated summary element traced back to the source utterance. Audit-and-trust layer over episodic memory. Built on proprietary 1.5M+ medical-encounter dataset.
- ASAPP GenerativeAgent T1
Treats memory as first-class architecture. Captures the digital footprint of every interaction; retrieves preference and history at engagement time. Public example: airline knowing a frequent flyer wants aisle seats with her son — preference-aware, not just history-lookup.
- BenevolentAI T1
Taken private: merged into Osaka Holdings (renamed BenevolentAI S.A.) and delisted from Euronext Amsterdam 2025-03-13. Target identification / drug repurposing / mechanism tracing. 85+ data sources, petabyte-scale, rebuilt every few weeks. Wet-lab results re-enter the graph and shift downstream predictions — institutional experimental memory closing a feedback loop. As of Oct 2026 benevolent.com leads with Qor, powered by BenevolentAI, a life-science intelligence service for biopharma decision makers and consultancies. Qor (qor.one) is a continuously updated decision-intelligence service built on BenevolentAI's knowledge graph and reasoning methods: it tracks evidence on an asset or indication (competitive position, rival readouts, comparable deals), source-verifies each claim and flags when an earlier conclusion stops holding. It targets biotech teams and life-science consultancies.
- Causaly T1
Agentic AI platform for life sciences: orchestrated scientific agents over a curated biomedical knowledge graph (plus Bio Graph and Pipeline Graph), an evidence-retrieval system and an enterprise data fabric over literature, trials and patents.
Sources (29 cited facts, 5 third-party)
Each fact links to the page it came from; the badge says who published it (how to read sources).
- What it is In-context real-time memory + live data collection vendor
- What it does & what's distinct Real-time simultaneous inference + data collection — dynamically updates in-context repr… vendor
- Claims / benefits ~$30M ARR within months of 2025 commercial launch. $1.4B raised at >$14B (Jan 2026). vendor
- Modalities vision + sensor vendor
- Created 2023 (Skild AI founded 2023 by Deepak Pathak and Abhinav Gupta; Pittsburgh PA) third-party
- Funding latest: $1.4B Series C at ›$14B valuation (SoftBank lead, 2026-01); prior $300M Series A… vendor
- Customers / scale 51-200 ppl Samsung, LG, Schneider, CommonSpirit, Salesforce Ventures (strategic investors) vendor
- Pricing No public pricing; $4k–$15k target hardware cost enabled by Skild Brain third-party
- Compliance Complex multi-jurisdiction compliance landscape (38 state AI laws + EU AI Act) vendor
- Data handling 4-source data flywheel: simulation + internet video + teleoperation + real deployments vendor
- Deployment Cloud inference + on-robot edge deployment vendor
- HQ US (Pittsburgh PA) third-party
- Founders / pedigree Deepak Pathak (CEO) and Abhinav Gupta (President); Carnegie Mellon professors third-party
- Memory volume / scale internal — undisclosed ($30M ARR; $14B valuation) vendor
- Versioning model-version semantics (policy checkpoints) vendor
- Namespace primitives robot-per-instance (per-robot memory) vendor
- Contradiction handling always overwrite (last-write-wins) vendor
- Forgetting policy episode-based memory; long-term memory module retains landmarks; episodic memory pruned … vendor
- Validated verticals robotics (humanoid, manipulation), autonomous-driving, embodied AI research vendor
- Time to running weeks-to-months (custom robot/vehicle integration) or research-only code release vendor
- Anti-fit not for non-embodied / non-physical use cases vendor
- Optimised for real-time perception + spatial reasoning + multi-modal sensor fusion vendor
- Adjacent infrastructure requires robot / vehicle hardware + sensor stack vendor
- Pros Real-time in-context adaptation — robot updates representation as it acts, instead of re… vendor
- Cons Robot-specific; rapid in-context updates raise stability concerns under distribution shi… vendor
- Project & sources Skild brain blog vendor
- licensing-bucket commercial third-party
- positioning-platform-vs-product platform vendor
- taxonomy-three-layer-rollup agent-infra repo
What changed
Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)