AnrakConductor: Ensemble
anrak-conductor-ensembleanrak/conductor-ensembleThe same grounded Indian-law pipeline as AnrakConductor, with the routing removed: every question goes to all four jurists in parallel. Athena, Vikram, Themis and Chanakya are deliberately different model families, so their errors are largely independent — the condition under which fan-out plus verifier aggregation actually beats a single strong model. A senior-partner aggregator consolidates the drafts and the three-cop panel cross-examines the result against retrieved authority.
The Panel
Four independent jurists draft the same question in parallel. They are deliberately different model families, so their errors are largely independent — the condition under which fan-out plus aggregation actually beats one strong model.
| Jurist | Lens | What it contributes |
|---|---|---|
| Athena | All-round legal drafter | Decomposes the question and covers every sub-issue methodically. Usually the most complete draft. |
| Vikram | Frontier reasoner | Pushes maximum depth on the hardest part of the problem. The rollout engine for deep search. |
| Themis | Deep reasoning specialist | Careful step-by-step chains that flag their own uncertainty rather than leaping to a conclusion. |
| Chanakya | Indian-law native | Trained closest to Indian legal language and drafting convention; on the pure family, the practical-implications lens. |
Pricing
One flat charge per call, whatever the answer's length. A request to this id runs ~8 underlying model calls plus live legal research — that fan-out, not your token count, is what it costs us, so that is what we price on.
Estimate a month
Requests per month to anrak-conductor-ensemble.
- Per request
- ₹53.63
- Per month
- ₹16,08,900
- Per 1,000 calls
- ₹53,630
Comparing against a per-token model?
On a reference request (2,000 tokens in, 2,000 out) this price works out to an effective $60.94 / $243.77 per 1M tokens.
That number looks high next to a raw frontier model, and it should: a raw model bills you for one call, while this id bills for 8 plus retrieval and a verification pass. We publish the comparison rather than hide it — but we bill per request, so a long answer does not cost you more.
Verification
Three-cop verifier panel
A Citation Cop, a Logic Cop and a Statute Cop cross-examine the consolidated answer against the authorities that were actually retrieved. Flagged fabrications are corrected before the answer returns; if the panel cannot reach quorum, the answer is withheld rather than shipped unverified.
The verdict rides on every response as anrak.verify, the drafts and their grounded scores as anrak.orchestration, and the ordered trace as anrak.reasoning. When streaming, the same narration arrives live as delta.reasoning_content.
Quickstart
Two changes from an ordinary OpenAI call: the base_url and your ANRAK- key.
from openai import OpenAI
client = OpenAI(
base_url="https://anrak.legal/api/v1",
api_key="ANRAK-xxxxx",
)
resp = client.chat.completions.create(
model="anrak-conductor-ensemble",
messages=[{"role": "user", "content": "Can a Section 138 NI Act complaint be quashed if the debt is time-barred?"}],
)
print(resp.choices[0].message.content)
# What it cost, and whether a downgrade happened:
extra = resp.model_extra or {}
print(extra["anrak"]["billing"]) # {'model': 'anrak-conductor-ensemble', 'price': '₹53.63', ...}
print(extra["anrak"]["downgraded"]) # None unless the pipeline was downgradedLimits and trade-offs
- Materially slower than the router — four drafters, a merge and three cops run per call.
- On a genuine one-line lookup this spends the full panel on a question the router would have answered solo.
Best for
- • Opinions and advice where a missed authority is expensive
- • Reproducible depth — the bench convenes on every call, no routing variance
- • Evaluation runs where you want the ceiling of the pipeline, not its average