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How Asthra compares

Chat vs. RAG vs. the Asthra studio.

Three categories of tool show up in evaluations: general-purpose chat assistants, in-house RAG builds, and content-management add-ons. Here's where each one breaks down — and where the chat-native studio purpose-built for regulatory writing earns its keep.

Side-by-side

What matters in regulated writing.

Capability
Generic AI chat
In-house RAG build
Asthra
Studio surface
Chat-native authoring inside the document
~Chat only, no document context
×Form-based UI, not chat-native
Section overview, freeform chat, approval gates — one surface
Walk-away drafting (run-and-return)
×
×
Background run, return to bundle in 1–2h
Mid-draft literature search (PubMed / CT.gov / bioRxiv)
~Open-internet, no provenance
×
Approval-gated, ledger-logged
Agent-driven data analysis over line listings & sales data
×LLM-fabricated arithmetic, no audit
×
Deterministic Python, every step audit-logged, table/figure output
Reusable reviewer personas / skills
×
×
FDA Clinical, CMC, CER Device, CSR Writer QC
End-of-run QC report
×
×
Structured quality pass on every run
Audit-ready run bundles
×
×
Draft + provenance trail + QC + reproducibility metadata
Grounding & provenance
Closed-system drafting; internet access gated
×Open by default; falls back to training memory
~Depends on implementation
Closed by default; writer-approval gate, ledger-logged
Sentence-level citations to your sources
×Best-effort, often invented
~Document-level only, typically
Document + sentence, on demand
Explicit gap flags for missing data
×Fills gaps with plausible text
×Surfaces nothing
Inline, ledger-recorded
Hyperlinks resolved at draft time (eCTD B21)
×
×Publishing-phase fixup
Anchored at write time, re-derives on reorder
Regulated writing fit
Module-specific writing rules (ICH E3, MDR, M4Q)
×
~Custom-built per module
Built in
Writes into your house templates
×
~Often markdown output
Native .docx with styles
Lives inside Microsoft Word
×Separate browser app
×Custom UI
Word add-in
Audit & compliance
Append-only audit ledger
×
~If you build it
Embedded in .docx
Survives the vendor (artifacts portable)
×
~Depends on architecture
By design
Operations
Time to first usable draft
Hours, but not trustworthy
×6–12 months to build
Days, with provenance
Maintenance & model upgrades
Vendor handles
×Your team's burden
Vendor handles, validated
Why this matters

Three things only
a purpose-built tool gets right.

REASON / 01

Closed-system retrieval is architectural

You can't bolt it onto a general chatbot. The drafting agent has to be designed without internet access from day one — and we built Asthra that way.

REASON / 02

Module rules aren't prompts

ICH E3, MDR, M4Q aren't style preferences — they're document obligations. Asthra encodes them as validated rules per module, not free-text prompts that drift across runs.

REASON / 03

Audit readiness lives with the document

The ledger embeds in the .docx. It survives offline, vendor changes, and regulatory archival. That's a regulated-writing property, not an analytics dashboard.

Try it on a real CSR.

30-day pilot. We benchmark Asthra's output against whatever you're using today — generic AI, in-house build, or manual.