{
  "date": "2026-09-06",
  "objective": "Research evidence and useful tools",
  "projects": [
    {
      "id": "loopscope",
      "name": "Loopscope",
      "status": "Owner-designated flagship; beta; daily personal use reported",
      "market": "Local inspection and replay of agent workflows for individual builders and small research teams.",
      "scores": [
        4,
        3,
        4,
        4,
        4
      ],
      "forces": [
        "LangSmith and Langfuse already address tracing and evaluation. Their breadth raises the bar; Loopscope competes on setup burden and legibility of live loops, not trace-platform breadth.",
        "LangGraph and its event interfaces shape compatibility. Open source reduces contractual lock-in, but maintaining hooks through upstream changes still costs founder time.",
        "Developers can choose free tools and readily replace a small hook. Daily personal use establishes internal utility; willingness to pay and independent adoption remain unmeasured.",
        "A basic dashboard is easy to reproduce. Reliable replay, bounded overhead and clear nested-run behavior take more work, but are not yet a durable entry barrier.",
        "Console logs, JSONL inspection and framework-native traces can solve the immediate debugging job without another dashboard."
      ],
      "refs": [
        "smith",
        "fuse"
      ],
      "wedge": "A tiny, local, failure-tolerant instrument with a reproducible example of finding an otherwise costly failure.",
      "first": "Make Loopscope the lead practical-tool flagship.",
      "amend": "Keep it a lead, but use Nightshift as one demanding reference workflow. Do not build a second general observability platform. Internal integration is a testbed, not independent market validation.",
      "human": "Time one real diagnosis with and without replay; prepare a clean-install exercise for an outside user.",
      "night": "One bounded replay or nested-run regression with a failing fixture, passing check and replay artifact.",
      "gate": "After two weekly cycles, retain development priority only if diagnosis time improves or an outside user completes the example and identifies a concrete need.",
      "allocation": 25,
      "group": "Focus",
      "confidence": "Medium: usage attributed; market position inferred",
      "repo": "https://github.com/sw30labs/loopscope",
      "pressure": 3.8,
      "sources": [
        {
          "title": "LangSmith observability",
          "url": "https://www.langchain.com/langsmith/observability"
        },
        {
          "title": "Langfuse self hosting",
          "url": "https://langfuse.com/self-hosting"
        },
        {
          "title": "Loopscope repository",
          "url": "https://github.com/sw30labs/loopscope"
        }
      ]
    },
    {
      "id": "nightshift",
      "name": "Nightshift",
      "status": "Research Engine flagship; implemented local workflow; net time savings under evaluation",
      "market": "Bounded overnight code maintenance across a solo builder\u2019s repository portfolio.",
      "scores": [
        5,
        4,
        4,
        5,
        5
      ],
      "forces": [
        "OpenHands and the broader coding-agent category compete for delegated development work. A writer/critic loop by itself is readily substitutable; the narrow portfolio contract is the stronger differentiator.",
        "Useful output depends on model quality, serving stacks and local hardware. Separate writer and critic endpoints do not guarantee independent errors or effective criticism.",
        "A solo developer can switch harnesses or work interactively. The relevant purchase decision is attention: every rejected branch and long review reduces value.",
        "Open frameworks make it inexpensive to assemble overnight loops. A trustworthy record of accepted changes and measured review cost is harder to replicate than the interface.",
        "Interactive coding assistants, scripted maintenance and leaving low-value work undone can all outperform unattended work once review and repair time are counted."
      ],
      "refs": [
        "hands",
        "ds4"
      ],
      "wedge": "Frozen small briefs, host-verified checks, reviewable branches and useful cross-repository memory.",
      "first": "Assess as a crowded coding-agent product with uncertain external demand.",
      "amend": "Designate as a cross-cutting Research Engine flagship for internal capacity, while keeping commercial ambition conditional. Limit self-improvement so the engine does not consume the lab.",
      "human": "Review accepted outcomes and log minutes spent specifying, reviewing and repairing. Choose tasks by portfolio priority, not repository recency alone.",
      "night": "Start with one target and two checkable jobs per night. Produce branch, test log, summary and accepted/rejected outcome; run sequentially on shared hardware.",
      "gate": "Over two weeks, require positive net human time saved and no material scope violation. Count failed and abandoned runs. Pause expansion if review backlog exceeds one morning session.",
      "allocation": 15,
      "group": "Focus",
      "confidence": "Medium on implementation; low on net savings and demand",
      "repo": "https://github.com/sw30labs/nightshift",
      "pressure": 4.6,
      "sources": [
        {
          "title": "OpenHands",
          "url": "https://github.com/OpenHands/OpenHands"
        },
        {
          "title": "DwarfStar inference engine",
          "url": "https://github.com/antirez/ds4"
        },
        {
          "title": "Nightshift repository",
          "url": "https://github.com/sw30labs/nightshift"
        }
      ]
    },
    {
      "id": "oscal-skills-guardrails",
      "name": "OSCAL Skills Guardrails",
      "status": "Evidence-selected flagship; reference implementation with hardening gaps",
      "market": "Policy-driven admission and integrity evidence for organizations adopting executable agent skills.",
      "scores": [
        4,
        3,
        4,
        4,
        4
      ],
      "forces": [
        "Cisco Skill Scanner already combines static, semantic and behavioral checks. Dual evidence alone is weak differentiation; policy linkage and content-bound decisions are the plausible niche.",
        "NIST OSCAL is a public data standard, reducing dependence on a proprietary schema. Scanner and judge changes still affect evidence consistency and maintenance.",
        "Security teams demand demonstrable false-positive rates, enforcement and usable evidence. They can prefer existing scanners or postpone adoption; no paying design partner was evidenced.",
        "Adding a policy wrapper is relatively easy. Robust mutation handling, digest-bound approvals and independently reproducible evaluation create a higher practical barrier.",
        "Manual skill review, allowlists, restricted execution and existing CI scanners can satisfy parts of the job. Admission scanning cannot substitute for runtime containment."
      ],
      "refs": [
        "cisco",
        "oscal"
      ],
      "wedge": "Reproducible, digest-bound admission decisions with inspectable OSCAL evidence, rather than a promise of universal detection.",
      "first": "Prioritize hardening and a clean/adversarial evaluation over feature growth.",
      "amend": "Retain as the primary security experiment. Reuse a bounded Nightshift fixture to test policies, but do not call Nightshift governed until the enforcement path is implemented and checked.",
      "human": "Freeze acceptance criteria and review adversarial labels, mutation behavior and false positives.",
      "night": "Build a corpus harness and regression fixtures for malformed judge output, changed content after approval and symlink cases.",
      "gate": "Require deterministic integrity cases to pass and report semantic misses and false positives separately. A reproducible bypass blocks a security-readiness claim; it is a useful research result.",
      "allocation": 20,
      "group": "Focus",
      "confidence": "Medium: artifacts inspected; enforcement and general detection unverified",
      "repo": "https://github.com/sw30labs/oscal-skills-guardrails",
      "pressure": 3.8,
      "sources": [
        {
          "title": "Cisco Skill Scanner",
          "url": "https://github.com/cisco-ai-defense/skill-scanner"
        },
        {
          "title": "NIST OSCAL model overview",
          "url": "https://www.nist.gov/system/files/documents/2021/02/25/Day1.1-Michaela-OSCAL%20Overview.pdf"
        },
        {
          "title": "OSCAL Skills Guardrails repository",
          "url": "https://github.com/sw30labs/oscal-skills-guardrails"
        }
      ]
    },
    {
      "id": "tslit-dspy-dgx",
      "name": "TSLIT-DSPy DGX",
      "status": "Evidence-selected experimental flagship; negative and withdrawn results preserved",
      "market": "Controlled model-integrity experiments for researchers investigating identity/date-conditioned behavior.",
      "scores": [
        4,
        4,
        4,
        3,
        4
      ],
      "forces": [
        "Garak and Promptfoo provide broad vulnerability/evaluation tooling. TSLIT\u2019s opportunity is a rigorous narrow experiment, not broader scanner coverage.",
        "Model releases, inference configuration and an independent detector determine reproducibility. Limited positive ground truth makes evaluation data a scarce input.",
        "Researchers can run their own probes and require strong controls before relying on a detector. An all-negative holdout does not demonstrate sensitivity.",
        "Prompt variants are easy to create; carefully matched controls, frozen traces and independent reproduction are more difficult and more valuable.",
        "General vulnerability probes, manual paired analysis and provenance review address adjacent integrity concerns, often without a dedicated system."
      ],
      "refs": [
        "garak",
        "promptfoo"
      ],
      "wedge": "A falsifiable, carefully controlled study of a specific conditional behavior.",
      "first": "One replication before extending detection claims.",
      "amend": "Move to a rotating evidence slot. A shared evidence format with Guardrails is useful, but combining outputs must not launder weak detection into a stronger security claim.",
      "human": "Review the short cert_expiry cell and matched controls; distinguish truncation from a repeatable behavioral effect.",
      "night": "Run frozen matched conditions with repeated seeds; retain raw outputs and configuration without rewriting holdouts.",
      "gate": "If the anomaly does not reproduce, publish a negative finding and stop expansion. If it does, require independent confirmation before describing a trigger.",
      "allocation": 0,
      "group": "Rotate",
      "confidence": "Low: small evaluation and weak detector evidence",
      "repo": "https://github.com/sw30labs/tslit-dspy-dgx",
      "pressure": 3.8,
      "sources": [
        {
          "title": "NVIDIA garak",
          "url": "https://github.com/NVIDIA/garak"
        },
        {
          "title": "Promptfoo",
          "url": "https://github.com/promptfoo/promptfoo"
        },
        {
          "title": "TSLIT-DSPy DGX repository",
          "url": "https://github.com/sw30labs/tslit-dspy-dgx"
        }
      ]
    },
    {
      "id": "wiki-vs-rag",
      "name": "Wiki vs RAG",
      "status": "Evidence-selected flagship; four-arm study on one corpus",
      "market": "Reproducible retrieval-strategy comparisons for builders selecting knowledge workflows.",
      "scores": [
        4,
        3,
        4,
        5,
        5
      ],
      "forces": [
        "Ragas and Promptfoo already support evaluation workflows. The useful contribution is a transparent comparison and dataset, not another evaluation product.",
        "Embedding models, generators and judges influence rankings. Open tooling offers alternatives, but upgrades can change comparability.",
        "Builders need results on their own corpus. A single-corpus conclusion transfers poorly, giving potential adopters strong reasons to rerun or ignore it.",
        "A comparison notebook is cheap to create. High-quality human labels, repeated runs and independently reproducible costs are harder to establish.",
        "Small hand-labeled tests, existing evaluation libraries and pragmatic single-shot retrieval can answer the decision without a separate project."
      ],
      "refs": [
        "ragas",
        "promptfoo"
      ],
      "wedge": "Decision-grade tradeoffs with explicit uncertainty and full indexing, retrieval and generation costs.",
      "first": "Repeat the frozen study and add a second corpus.",
      "amend": "Treat it as reusable Research Engine methodology and a rotating publication asset. Do not duplicate an evaluation framework or infer a universal winner.",
      "human": "Audit a blinded sample of judge results; choose a second corpus that could reverse the original finding.",
      "night": "Reproduce the frozen questions, capture failures and compute per-strategy distributions and confidence intervals.",
      "gate": "If rankings change materially across seeds or corpora, report conditional guidance. End the study when it supports an actionable retrieval choice.",
      "allocation": 0,
      "group": "Rotate",
      "confidence": "Medium for recorded comparison; low external validity",
      "repo": "https://github.com/sw30labs/wiki-vs-rag",
      "pressure": 4.2,
      "sources": [
        {
          "title": "Ragas",
          "url": "https://github.com/vibrantlabsai/ragas"
        },
        {
          "title": "Promptfoo",
          "url": "https://github.com/promptfoo/promptfoo"
        },
        {
          "title": "Wiki vs RAG repository",
          "url": "https://github.com/sw30labs/wiki-vs-rag"
        }
      ]
    },
    {
      "id": "singularity-atlas",
      "name": "Singularity Atlas",
      "status": "Featured working dashboard; practical value provisional",
      "market": "AI infrastructure and convergence monitoring for independent researchers and technical writers.",
      "scores": [
        4,
        4,
        5,
        5,
        5
      ],
      "forces": [
        "Epoch publishes AI models, data-center and company datasets. Atlas competes for attention with specialist research feeds; a globe and composite index alone do not establish added decision value.",
        "Upstream public feeds control availability, definitions and revisions. Open access does not imply permanent availability or unrestricted redistribution.",
        "Readers can follow primary sources directly. Their switching costs are low and evidence of recurring outside use or willingness to pay was not found in the inspected material.",
        "Feed aggregation and brief generation are accessible capabilities. A differentiated curated dataset and documented corrections would be stronger barriers.",
        "RSS, newsletters, bookmarks and direct dataset queries provide situational awareness without running another service."
      ],
      "refs": [
        "epoch"
      ],
      "wedge": "A provenance-linked brief that changes a concrete research or writing decision.",
      "first": "Keep the working dashboard; verify the value of its synthesis.",
      "amend": "Use as the lab\u2019s bounded intelligence input and distribution aid. Cap dashboard development; distinguish its editorial index from a calibrated forecast.",
      "human": "For one week, record which sourced signals change a project decision or produce a useful article angle.",
      "night": "Check feed freshness, broken sources and duplicate stories; draft a short brief with source links for human review.",
      "gate": "Retain weekly maintenance only if useful signals outweigh reading and upkeep time; otherwise use a simpler feed list.",
      "allocation": 5,
      "group": "Maintain",
      "confidence": "Low: dashboard exists; decision value unmeasured",
      "repo": "https://github.com/sw30labs/singularity-atlas",
      "pressure": 4.6,
      "sources": [
        {
          "title": "Epoch AI datasets",
          "url": "https://epoch.ai/data"
        },
        {
          "title": "Singularity Atlas repository",
          "url": "https://github.com/sw30labs/singularity-atlas"
        }
      ]
    },
    {
      "id": "videocortex",
      "name": "VideoCortex",
      "status": "Featured PoC; local TRIBE v2 research instrument",
      "market": "Local stimulus-to-predicted-brain-response tooling for neuroscience exploration and teaching.",
      "scores": [
        3,
        5,
        4,
        4,
        4
      ],
      "forces": [
        "The upstream TRIBE v2 notebook and demo already offer the underlying scientific capability. Local preflight, platform support and clearer figures are the instrument\u2019s value.",
        "TRIBE v2 is the central model dependency and its repository specifies CC-BY-NC-4.0. That materially constrains assuming a straightforward commercial offering; replacing the core would be costly.",
        "Researchers can use the upstream notebook and demand validity for their study. Attractive cortical plots are insufficient evidence of practical or personalized accuracy.",
        "A visual wrapper is relatively accessible; numerical parity, timing correctness and trustworthy cross-device behavior require more careful work.",
        "Upstream notebooks, generic cortical visualization and simpler stimulus analysis can address teaching or exploratory needs without this package."
      ],
      "refs": [
        "tribe"
      ],
      "wedge": "A reproducible local instrument with explicit average-subject limits and verified output parity.",
      "first": "Explore practical value through a narrowly defined research use case.",
      "amend": "Keep as a research/teaching option and rotate only for a parity or user-validation experiment. Do not frame it as generic video understanding or individualized neuroscience.",
      "human": "Choose one research/teaching task and review real versus synthetic output and licensing dependencies.",
      "night": "Prepare a pinned reference fixture and compare supported backends within an explicitly chosen numerical tolerance.",
      "gate": "No promotion beyond PoC until a real use case and upstream parity are demonstrated. Commercial prioritization requires resolving applicable permissions first.",
      "allocation": 0,
      "group": "Rotate",
      "confidence": "Medium for dependency and scope; low for practical demand",
      "repo": "https://github.com/sw30labs/videocortex",
      "pressure": 4.0,
      "sources": [
        {
          "title": "Meta TRIBE v2 and license",
          "url": "https://github.com/facebookresearch/tribev2"
        },
        {
          "title": "VideoCortex repository",
          "url": "https://github.com/sw30labs/videocortex"
        }
      ]
    },
    {
      "id": "AI-OS-1",
      "name": "AI-OS-1",
      "status": "Featured design corpus; no runtime",
      "market": "Model-aware scheduling and placement for bandwidth-constrained local multi-node inference.",
      "scores": [
        5,
        5,
        4,
        3,
        5
      ],
      "forces": [
        "DwarfStar supplies the native engine and vLLM already documents multi-node parallelism. An OS-sized design must beat a simple engine configuration on a specified workload to justify itself.",
        "The hardware interconnect, engine interfaces and model architecture tightly constrain implementation. Supporting all three creates concentrated technical dependency.",
        "Local operators can keep a model on one box or use established engines. They need measured latency, throughput and capacity improvements before adopting another control layer.",
        "A robust scheduler has meaningful engineering barriers, but capable engine maintainers can incorporate useful optimizations. A design document alone does not create that barrier.",
        "Single-node serving, static placement and existing tensor/pipeline parallelism can eliminate the need for a new system layer."
      ],
      "refs": [
        "vllm",
        "ds4"
      ],
      "wedge": "One independently reproducible placement improvement on existing Sparks, with end-to-end benefit.",
      "first": "Run Phase 0 before writing the runtime.",
      "amend": "Make this an infrastructure option. Promote only if measurements identify a bottleneck that also materially limits useful Nightshift work; avoid a hardware rewrite driven by theoretical elegance.",
      "human": "Approve a fixed workload, single-node baseline and decision threshold before a placement comparison.",
      "night": "Prepare reproducible measurement scripts and manifests; reserve hardware measurements for an exclusive slot, separate from overnight coding.",
      "gate": "If an existing engine configuration meets the workload need, stop at the evidence report. A proposed 20% useful-work improvement is a planning threshold to agree before testing, not an achieved result.",
      "allocation": 0,
      "group": "Gate",
      "confidence": "Low: design only; no performance advantage established",
      "repo": "https://github.com/sw30labs/AI-OS-1",
      "pressure": 4.4,
      "sources": [
        {
          "title": "vLLM parallelism and scaling",
          "url": "https://docs.vllm.ai/en/latest/serving/parallelism_scaling/"
        },
        {
          "title": "DwarfStar inference engine",
          "url": "https://github.com/antirez/ds4"
        },
        {
          "title": "AI-OS-1 repository",
          "url": "https://github.com/sw30labs/AI-OS-1"
        }
      ]
    },
    {
      "id": "aegis-research",
      "name": "AEGIS",
      "status": "Featured research proposal; no implementation or measured performance",
      "market": "Locally operated, governed security assessment for teams needing reproducible scoped workflows.",
      "scores": [
        5,
        4,
        5,
        3,
        5
      ],
      "forces": [
        "Pentera addresses automated security validation; existing security tools and service providers bring experience and trust. A new appliance must demonstrate a specific unmet workflow.",
        "Hardware, local models and tool integrations create several maintenance dependencies. Specialized hardware would add servicing and supply constraints before demand is established.",
        "Security teams can choose existing services and require auditable scope control. Procurement and trust requirements create substantial adoption friction for an unimplemented proposal.",
        "Prototypes are accessible; dependable enforcement, recovery and service support are much harder. These barriers burden AEGIS now rather than protect it.",
        "A commodity workstation, existing assessment tools and a human-reviewed playbook may meet the same need with less integration risk."
      ],
      "refs": [
        "pentera",
        "cisco"
      ],
      "wedge": "A small software reference proving scope enforcement and evidence capture on an authorized synthetic target.",
      "first": "Start a software reference on existing hardware.",
      "amend": "Defer active build until a concrete user workflow is validated. Reuse Guardrails findings, but do not assume admission control proves tool mediation or that named research connections are integrations.",
      "human": "Validate one operator need and specify a minimal authorized target and forbidden actions.",
      "night": "Only after that gate: prepare synthetic fixtures and testable enforcement acceptance cases.",
      "gate": "No appliance/custom-silicon work before the reference demonstrates value beyond existing tools and the operator need is confirmed.",
      "allocation": 0,
      "group": "Gate",
      "confidence": "Low: proposal; market demand unvalidated",
      "repo": "https://github.com/sw30labs/aegis-research",
      "pressure": 4.4,
      "sources": [
        {
          "title": "Pentera security validation solution brief",
          "url": "https://pentera.io/wp-content/uploads/2026/04/security_validation_for_the_financial_industry.pdf"
        },
        {
          "title": "Cisco Skill Scanner",
          "url": "https://github.com/cisco-ai-defense/skill-scanner"
        },
        {
          "title": "AEGIS repository",
          "url": "https://github.com/sw30labs/aegis-research"
        }
      ]
    },
    {
      "id": "rpc-h16",
      "name": "RPC-H16",
      "status": "Frontier flagship; initial software experiment, physical concept unproven",
      "market": "Early fault-tolerant optical architecture research; future adopter segment remains hypothetical.",
      "scores": [
        4,
        5,
        5,
        2,
        5
      ],
      "forces": [
        "Photonic interconnect suppliers such as Lightmatter illustrate a developed adjacent ecosystem, not direct validation or competition for the same H16 logic. Research groups and conventional architectures compete for attention and future application fit.",
        "A physical path would depend on optical components, alignment, detectors and fabrication access. The present software experiment has much lower supplier exposure than a future device.",
        "Any future integrator would require end-to-end reliability, energy and useful-computation evidence. No validated buyer segment or procurement path is established.",
        "Physical optical systems have high entry barriers, hence relatively low entrant threat. Those same barriers make commercialization difficult for a solo lab; they are not evidence of a moat here.",
        "Electronic fault tolerance, conventional routing and simpler redundant systems set the baseline. Optical transport alone does not demonstrate a superior computing system."
      ],
      "refs": [
        "light"
      ],
      "wedge": "A small falsifiable result about physically feasible channel mappings and failure behavior.",
      "first": "Protect a bounded frontier experiment despite weak near-term commercial attractiveness.",
      "amend": "Preserve a 10% curiosity allocation instead of ranking it as a near-term product. Separate software evidence from physical feasibility; do not use high hardware barriers as a reason to overinvest.",
      "human": "Specify physical node bodies, line-of-sight/clearance rules and channel mapping for E002; interpret the result.",
      "night": "Create deterministic geometry fixtures and a reproducible report once the human approves assumptions; no model in the numerical decision path.",
      "gate": "After one bounded E002 cycle, record feasible/infeasible under stated assumptions. Stop geometry expansion if the model adds complexity without discriminating among designs.",
      "allocation": 10,
      "group": "Frontier",
      "confidence": "Very low commercial confidence; early software evidence only",
      "repo": "https://github.com/sw30labs/.github/blob/main/research/flagships.md#frontier-flagship-rpc-h16",
      "pressure": 4.2,
      "sources": [
        {
          "title": "Lightmatter photonic interconnect platform",
          "url": "https://lightmatter.co/products/passage"
        },
        {
          "title": "RPC-H16 public research brief",
          "url": "https://github.com/sw30labs/.github/blob/main/research/flagships.md#frontier-flagship-rpc-h16"
        }
      ]
    }
  ],
  "sources": {
    "profile": [
      "Live SW30 Labs profile",
      "https://github.com/sw30labs/.github/blob/main/profile/README.md"
    ],
    "dossiers": [
      "SW30 evidence dossiers",
      "https://github.com/sw30labs/.github/blob/main/research/flagships.md"
    ],
    "porter": [
      "Harvard: The Five Forces",
      "https://www.isc.hbs.edu/strategy/business-strategy/Pages/the-five-forces.aspx"
    ],
    "smith": [
      "LangSmith observability",
      "https://www.langchain.com/langsmith/observability"
    ],
    "fuse": [
      "Langfuse self hosting",
      "https://langfuse.com/self-hosting"
    ],
    "cisco": [
      "Cisco Skill Scanner",
      "https://github.com/cisco-ai-defense/skill-scanner"
    ],
    "oscal": [
      "NIST OSCAL model overview",
      "https://www.nist.gov/system/files/documents/2021/02/25/Day1.1-Michaela-OSCAL%20Overview.pdf"
    ],
    "garak": [
      "NVIDIA garak",
      "https://github.com/NVIDIA/garak"
    ],
    "promptfoo": [
      "Promptfoo",
      "https://github.com/promptfoo/promptfoo"
    ],
    "ragas": [
      "Ragas",
      "https://github.com/vibrantlabsai/ragas"
    ],
    "tribe": [
      "Meta TRIBE v2 and license",
      "https://github.com/facebookresearch/tribev2"
    ],
    "epoch": [
      "Epoch AI datasets",
      "https://epoch.ai/data"
    ],
    "vllm": [
      "vLLM parallelism and scaling",
      "https://docs.vllm.ai/en/latest/serving/parallelism_scaling/"
    ],
    "ds4": [
      "DwarfStar inference engine",
      "https://github.com/antirez/ds4"
    ],
    "hands": [
      "OpenHands",
      "https://github.com/OpenHands/OpenHands"
    ],
    "pentera": [
      "Pentera security validation solution brief",
      "https://pentera.io/wp-content/uploads/2026/04/security_validation_for_the_financial_industry.pdf"
    ],
    "light": [
      "Lightmatter photonic interconnect platform",
      "https://lightmatter.co/products/passage"
    ]
  }
}