LLMs are great at reading and writing — but they fail at strict logic, compliance, and math. Holo Engine is the deterministic reasoning layer that makes your AI service safe for high-stakes Enterprise, Legal, and Financial markets.
Holo Engine doesn't replace compute — it replaces an entire class of infrastructure: vector DB, rule engine, graph DB, and ML classifiers. Plus eliminates the liability risk of hallucinated outputs. In one ~10 MB binary.
Get in touchStop losing high-stakes deals because of LLM hallucinations. Embed Holo Engine into your agentic loops to provide 100% mathematically verifiable outputs — the proof your enterprise clients demand.
LLMs approximate; Holo Engine calculates. Route complex logical deductions, contract rule verifications, and compliance checks through a deterministic core. Guarantee 100% mathematical accuracy for Legal, Tax, and HR agents where a single hallucinated clause can cause a lawsuit.
Don't let probabilistic models handle math or resource allocation. Holo Engine solves complex multi-constraint optimizations — from tax routing to supply chain logistics — instantly and deterministically, directly alongside your LLM pipeline.
Regulated industries demand explainability. Unlike neural networks where decisions are hidden in weights, Holo Engine provides a fully transparent, mathematically verifiable trace for every logical conclusion — prove exactly why your agent made a decision.
Holo Engine ships with its own Turing-complete scripting language — purpose-built for AI agents. Your LLM can write a logic program on the fly and execute it deterministically inside a fully isolated runtime, with guaranteed results and zero data leakage. No Python, no shell access, no security surface. The agent expresses complex business rules dynamically; Holo Engine runs them safely and returns a mathematically verified output.
Bring AI logic to your internal operations without massive cloud costs, data privacy risks, or GPU reliance. One binary, one API, zero dependencies.
A ~10 MB single Rust binary with zero runtime dependencies. Run complex logical inference directly on internal servers, IoT devices, or completely air-gapped networks — no cloud required.
Eliminate the need for complex pipelines combining vector databases, graph DBs, and ML classifiers. Holo Engine handles hierarchical reasoning, vectorless semantic routing, and anomaly detection in one deterministic API call.
Keep your proprietary logic and datasets strictly on-premise. No tokens sent to third-party APIs, no statistical leaking of your business rules — full sovereignty over your data.
Verified Use Cases
Zero-LLM Content Moderation
Classify prompt injections and hallucinations server-side. No external LLM calls in the loop.
# 1. Train the classifier
curl -X POST https://api.hiholo.ai/api/cognitive/observe \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"rows":[
{"role_override":"yes","sys_leak":"yes","encoding_trick":"no","label":"malicious"},
{"role_override":"no","sys_leak":"no","encoding_trick":"no","label":"safe"},
{"role_override":"yes","sys_leak":"no","encoding_trick":"yes","label":"malicious"},
{"role_override":"no","sys_leak":"yes","encoding_trick":"yes","label":"malicious"},
{"role_override":"no","sys_leak":"no","encoding_trick":"yes","label":"safe"}
],"target_key":"label"}'
# 2. Predict on unseen input
curl -X POST https://api.hiholo.ai/api/cognitive/predict \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"input":{"role_override":"yes","sys_leak":"yes","encoding_trick":"yes"}}'Agent Task Orchestration (CSP)
Map tool-assignment as a constraint satisfaction problem. Get a valid, deterministic plan — not an LLM guess.
# Solve 8 subtasks with all_diff constraint
curl -X POST https://api.hiholo.ai/api/solve \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"rows":[
{"subtask":"fetch_data","tool":null},
{"subtask":"parse_pdf","tool":null},
{"subtask":"extract_tables","tool":null},
{"subtask":"run_model","tool":null},
{"subtask":"validate","tool":null},
{"subtask":"summarize","tool":null},
{"subtask":"notify","tool":null},
{"subtask":"archive","tool":null}
],"target_key":"tool",
"domain":["http_client","pdf_extract","table_ocr","risk_engine","compliance","llm_writer","smtp","s3"],
"constraints":[{"type":"all_diff","scope":["*"]}],
"max_depth":100,"use_hints":true}'Compliance Policy Search
Semantic retrieval over hierarchical document corpora using hyperbolic geometry. No embeddings, no GPU.
# 1. Feed a policy document
curl -X POST https://api.hiholo.ai/api/feed_text \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"text":"Customer transaction logs must be retained for 7 years under SOX Section 802.",
"doc_id":"sox_retention",
"metadata":{"regulation":"sox","domain":"finance"}}'
# 2. Query
curl -X POST https://api.hiholo.ai/api/query_text \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"query":"transaction logs retention years SOX finance","k":3}'Real-Time Eval Drift Adaptation
Feed corrections into a running instance. The next request already uses updated logic — no redeployment.
# 1. Train: tone_verbose = pass
curl -X POST https://api.hiholo.ai/api/cognitive/observe \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"rows":[
{"format":"json","schema":"valid","tone":"verbose","verdict":"pass"},
{"format":"json","schema":"invalid","tone":"neutral","verdict":"fail"}
],"target_key":"verdict"}'
# 2. Predict → "pass"
curl -X POST https://api.hiholo.ai/api/cognitive/predict \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"input":{"format":"json","schema":"valid","tone":"verbose"}}'
# 3. Feed drift: tone_verbose = fail (3 examples)
curl -X POST https://api.hiholo.ai/api/cognitive/observe \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"rows":[
{"format":"json","schema":"valid","tone":"verbose","verdict":"fail"},
{"format":"json","schema":"valid","tone":"verbose","verdict":"fail"},
{"format":"json","schema":"valid","tone":"verbose","verdict":"fail"}
],"target_key":"verdict"}'
# 4. Predict again → now "fail" (instant adaptation)
curl -X POST https://api.hiholo.ai/api/cognitive/predict \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"input":{"format":"json","schema":"valid","tone":"verbose"}}'These are just a few examples. Holo Engine adapts to any deterministic workflow your agents need.
Discuss your scenario →Honest Benchmarks
Verified against scikit-learn, SciPy, python-constraint, TF-IDF, and BM25. No marketing fluff.
Where we dominate
Where we match
Where to use local tools
Holo is designed for compound multi-step execution. While an isolated math operation runs faster locally in Python, the moment you need classification + search + constraint solving in one workflow, Holo executes it server-side in a single call — no orchestration overhead, no inter-service latency.
Get in touch with us to discuss your enterprise AI needs.