GenAI Training & Alignment · SFT

The demonstrations
your model learns from.

Gold-standard prompt-response pairs, multi-turn dialogs, and tool-use traces — written and reviewed by domain experts so SFT yields a model that follows instructions and stays in character.

Capabilities

Built for production, not just demos.

  • Single-turn prompt-response demonstrations
  • Multi-turn dialog with consistent persona
  • Tool-use traces with function-call schemas
  • Code demonstrations across 12+ languages
  • Long-form (essay, summary, plan) demonstrations
  • Persona / style-guide adherence checks
  • Distill-from-stronger-model with human polish
  • Refusal + safe-completion demonstrations
Specs at a glance
Throughput30k demonstrations/wk
Token budgetUp to 32k context
Languages60+ (22 Indic + 40 global)
Domain expertsMD, JD, PhD, PE on-staff
Tool schemasJSON · OpenAI · Anthropic
DeliveryJSONL · HF Dataset · Parquet
Workflow

How a typical engagement runs.

Step 1

Spec

Lock the persona, style guide, refusal policy, and tool schemas.

Step 2

Seeds

Generate or import a seed prompt set; we sample for diversity + difficulty.

Step 3

Write

Domain experts compose gold answers; QA reviews each one.

Step 4

Polish

Editor pass for style + format consistency; lint against your house guide.

Step 5

Deliver

JSONL/HF dataset with per-record provenance + reviewer metadata.

Deliverables

What you get in your bucket.

Demonstration dataset (JSONL / HF Dataset / Parquet)
Per-record reviewer metadata + rationale
Style-guide adherence checks
Seed prompt corpus + diversity report
Persona / refusal policy library
Optional tool-schema validation
FAQ

Questions, answered.

Can you write demos for a niche domain?

Yes. We have MD, JD, PhD-CS, finance and tax-pro reviewers on staff. For specialised verticals (e.g. medical device, regulated finance), we add domain-vetted contractors with NDAs.

What about multi-turn dialog?

We support arbitrary-turn dialogs with consistent persona, memory-of-context, and a 'conversation goal' tag per session.

Tool-use / function-calling demonstrations?

Yes — we author traces against your tool schema (OpenAI / Anthropic / custom), with realistic error handling and multi-step reasoning.

Can you distill from a stronger model?

We support distill-then-polish: generate from a stronger model, then human reviewers correct + audit before inclusion.

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