AnrakConductor: Fast
anrak-conductor-fastanrak/conductor-fastA single pass through the grounded pipeline: planner, live research, citation manifest, one draft, then the three-cop verifier. No fan-out and no consolidation, so it returns in roughly the time of an ordinary chat completion while still answering from retrieved authority rather than model memory.
The Panel
This id runs a single pass — no panel convenes. One model answers, and the verifier reviews the result. For independent-error cancellation across four different model families, use anrak-conductor-ensemble.
Pricing
One flat charge per call, whatever the answer's length. A request to this id runs ~4 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-fast.
- Per request
- ₹25.73
- Per month
- ₹7,71,900
- Per 1,000 calls
- ₹25,730
Comparing against a per-token model?
On a reference request (2,000 tokens in, 2,000 out) this price works out to an effective $29.24 / $116.95 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 4 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-fast",
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-fast', 'price': '₹25.73', ...}
print(extra["anrak"]["downgraded"]) # None unless the pipeline was downgradedLimits and trade-offs
- One drafter means no independent-error cancellation — on a genuinely hard question the panel ids are meaningfully more reliable.
Best for
- • Lookups: limitation periods, section text, procedural steps
- • Drafting passes where grounding matters more than deliberation
- • Interactive UIs that cannot wait on a panel