Technology & models
Confident, specific, no hand-waving.
This page is for the technical evaluator. Value — custody and quality — always leads the plumbing. Here's the plumbing.
Three layers, plain language
Microfiber is one platform with three layers — we surface only the one a given buyer needs. Lead with the memory: it's the product; the utility is the foundation under it.
Private inference
The utility
A compliant, stateless model endpoint. Send context, get intelligence back. The foundation everything else sits on.
Your document corpus
The memory
Retrieval-grounded intelligence that knows your files and reasons across years of them. This is the product — the beachhead for accounting firms.
Your structured data
The query layer
Ask questions of data you already hold (transactions, records) — the model calls your own query function through the gateway and reasons over the exact results, never storing anything.
How Microfiber is built
A private endpoint, not a public chatbot.
Your firm integrates against api.microfiber.[tld] with your own key. Your application never talks to a public model provider — it talks to Microfiber.
Control plane vs. data plane.
Account, billing, and portal (no client data) are separated by design from the data plane — your documents, the vector store, retrieval, and prompt assembly — which runs inside a boundary we control. Inference runs inside that boundary on the owned-hardware tier; on the managed tier it runs at our contracted provider (see Security). This separation is a security control, not just an architecture choice.
Per-tenant isolation.
Every firm gets its own isolated environment. No shared memory, no commingled data, ever.
Stateless compute.
The model performs a computation and stores nothing. Your corpus and the intelligence about it live on our controlled side; raw horsepower is a utility we direct, never a place your data rests. On the managed tier, the excerpts needed to answer a query transit to that compute under a no-retention contract and are discarded after the response; on the owned-hardware tier the compute runs inside our boundary, so nothing transits at all.
Encryption in transit and at rest. Metadata-only logging.
We log that a request happened, never its contents.
Retrieval-grounded answers — the moat
Microfiber reasons over your documents, and the retrieval is built for the way financial and legal files are actually structured:
Structure-aware chunking
We split along sections, tables, and form fields — never blind fixed-size cuts that sever a number from its label.
Tables made reasoning-ready
Financial tables become narratives the model can reason over (e.g. “Asset X: 2024 depreciation $Y, method MACRS, accumulated $Z”) — the make-or-break capability for accounting work.
Hybrid retrieval
Semantic search and exact keyword/number matching and metadata filters (by client, document type, tax year), so “find the basis on this asset” lands on the right passage.
Re-ranking
Candidate passages are ordered by true relevance before the model ever sees them.
Citations, always
Every answer points back to the source document, page, and section.
Honest by design
When the answer isn't in your files, it says “I don't see that in your documents” instead of inventing a figure. For a firm where a wrong number is a real problem, that honesty is the product.
The separation, drawn03
The control plane and the data plane, separated by design.
Your documents, the vector store, retrieval, and prompt assembly live inside a boundary we control; what reaches the model at query time depends on your tier.
app + users · api.microfiber.[tld] with your key
auth · routing · metadata-only logging
your documents · cited answers
Your document corpus — stays inside a boundary we control.
stateless compute
calls only
prompt + retrieved chunks → ← answer
stateless utility · stores nothing · swappable
The control-plane / data-plane split — the trust story, made architectural.
Built to drop into your stack
Live todayclient = Anthropic(
base_url="https://api.microfiber.[tld]", # 1. point at Microfiber
api_key="sk-ac-...", # 2. your Microfiber key
)
client.messages.create(model="ac-qwen3-32b", ...) # 3. an Microfiber modelAn OpenAI-shape endpoint is under evaluation; today the API speaks the Anthropic Messages format.
A drop-in swap, not a rebuild.
If your tools already use the Anthropic SDK, switching to Microfiber is three lines — point the base URL at our endpoint, use your Microfiber key, name an Microfiber model. Your code doesn't change.
Models by alias, swapped server-side.
You call a stable Microfiber alias (e.g. ac-qwen3-32b); we map it to the right hosted model behind the scenes, so you're never re-integrating when the model layer advances.
Streaming responses.
Token-by-token streaming (server-sent events) is live and behaves exactly like the SDK's native streaming — no special handling.
Extended reasoning on demand.
Flip on “thinking” per request for harder problems on models that support it; off by default for speed.
The models
Microfiber runs leading open-weight models in a private environment — the key being that an open model, grounded on your own documents with strong retrieval, is what delivers accurate, cited answers on your work. We are not dependent on any single public AI vendor, and the model layer is swappable as the field advances.
We pick the right model for your work and host it privately — and because the model layer is swappable, you're never locked to one vendor's roadmap or pricing.
Representative models available (menu evolves as the ecosystem does):
- QwenLivestrong reasoning class — Qwen3-32B is serving in our environment today
- Llama (Meta)general-purpose workhorse class
- DeepSeekstrong reasoning / cost-efficient class
- Mistral / Mixtralefficient open models
- GPT-OSS-class open modelsas available
Why an open model wins on your documents.
Aren't the frontier models (ChatGPT, Claude) simply better? For general world knowledge, yes — they've read a huge slice of the public internet. But your client's tax return isn't on the internet. No model — frontier or not — was trained on your data; every model starts from zero on your files. So the question that actually matters isn't “which model knows the most about the world,” it's “which system reasons most accurately over your documents” — and there, research on financial documents is clear: retrieval and chunking quality drive answer accuracy more than the size of the model writing the answer. We give a strong open model your documents, precisely retrieved and cited; a frontier model handed a clumsy paste of those same files actually does worse.
Frontier models are smarter about the world; we're smarter about your data.
Enterprise / strictest tier
For firms with the highest custody requirements (e.g. healthcare PHI, or a strict closed-loop mandate), Microfiber offers a dedicated, owned-hardware deployment — full physical custody of both the data layer and the inference, with a certificate of destruction on offboarding. This is the only tier on which we can say your data never leaves the controlled environment: retrieval and inference both happen inside it, so nothing transits at query time.
For the evaluator
Take it apart on a call.
We're happy to go deep — architecture, retrieval, isolation, the model menu — and map every custody claim to your information security plan.