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Cogneros

Four ways to put AI into a professional firm.

Public assistants, vertical copilots, private deployment, or building it yourself — what each approach is good at, and how to tell which one your firm needs.

This compares approaches, not products. The names under each approach are illustrations, placed by the category each company publicly puts itself in — not a verified feature comparison, not a ranking, and not an endorsement. None of them were asked. If you are evaluating specific vendors, the questions worth putting to all of them are set out on the confidentiality page.

The four approaches

Ordered by how much of your own material each one can reach — which is the axis that actually separates them, and the one most comparisons leave out.

  1. 01

    Public assistants, used directly

    ChatGPT, Claude, Copilot or Gemini, used by your people much as they already are.

    Genuinely good at

    Immediate, inexpensive, and already happening whether or not anyone sanctioned it. For general drafting, for summarising a document somebody pastes in, and for thinking out loud, it is genuinely good — and the per-seat cost is a rounding error against any of the alternatives here.

    The trade

    It has no access to your material, so it cannot answer a question about what your firm has already done. It has no idea who is walled off from what. And unless you have deployed a governed tenancy, you have no record of what went into it — which is usually the discovery that starts the rest of this conversation.

    For exampleChatGPTClaudeMicrosoft CopilotGemini
  2. 02

    Vertical copilots and point tools

    Software that does one job inside one workflow extremely well — contract review, litigation drafting, discovery, diligence.

    Genuinely good at

    Depth, and proximity to the work. A tool built for clause review has seen more clauses than any general system ever will, and it lives inside the editor where the drafting actually happens rather than in another tab.

    The trade

    Scope is the trade. Each is bought per seat, each holds its own slice of your material, and none of them answers “what position has this firm taken on this issue, across every matter we have run”. Several tools also means several vendors holding your documents under several sets of terms.

    For exampleHarveyCoCounselSpellbookLuminanceClearbriefEverlaw
  3. 03

    Private deployment over your own material

    Where Cogneros sits

    A system built for one organization, indexing that organization's own repositories, answering under that organization's permissions, with the reasoning running where that organization says it runs.

    Genuinely good at

    It answers the questions nothing else can — about what your firm has already argued, decided, drafted and stood behind. Answers carry citations back to your own documents. Access follows the rules you already maintain, and where the work runs is a decision rather than a default.

    The trade

    It is a scoped engagement rather than a subscription, so it starts with a project and a number rather than a credit card. It assumes your material is in systems and that your permissions mean something. And it does not do the specialised depth a point tool does inside a single named workflow.

    For exampleCognerosPocono AIPrivity LabsLawFirmAutomateZanus AIIternal
  4. 04

    Build it yourself

    Assemble retrieval, a vector store, a model runtime and an interface from open-source parts.

    Genuinely good at

    Full control and no licence. For an organization with real engineering capacity and a reason to own the stack, it is a legitimate path, and the components are better every quarter.

    The trade

    You own retrieval quality, permission mapping, evaluation and the lifecycle — and the first three are where almost all the genuine difficulty in this category lives. A demo takes a weekend. Something a partner will rely on in front of a client takes considerably longer, and the maintenance does not stop.

    For exampleLlamaIndexLangChainOllamaCognee

Most firms end up with more than one. A public assistant under policy for general work, a point tool or two where a workflow justifies the depth, and a private layer over their own material for the questions only their own history can answer. The useful question is rarely which approach wins. It is which one you are currently missing.

How to choose

Five situations and what each one points at. Most firms recognise more than one, which is usually the answer in itself.

Your people need general help writing and thinking
A public assistant, under a written policy about what may be pasted into it. Start here; it is nearly free.
The job is one named, repeating workflow and the value is depth in it
A point tool built for that workflow. Nothing general will match it inside its own lane.
The value you are chasing is your own institutional knowledge
Private deployment over your own material. No amount of general capability substitutes for your own history.
Where the work physically runs is a real constraint
Private deployment, hybrid or on-premise. This is the constraint that rules the other three out.
You have engineering capacity and want to own the stack
Build it. Cost the ongoing half honestly, not just the build.

If private deployment is the one you are missing

Three questions decide it, and they come up in roughly this order. Each is answered at length rather than in a sentence.

Request a Private Demo

Or see how this reads in your own business — law firms, accounting and four more.

Your business has already built the knowledge.

Cogneros makes it available to the people who need it — under your permissions, traced to your own documents.

What an engagement costs

Engagements typically start at $35,000.

Scope follows the repositories you connect and where the system runs — cloud, hybrid, and on-premise are priced differently.

Prefer to talk?
+1 303-351-1691
Based in
Denver, Colorado

We use this only to arrange your demonstration. No documents are shared at this stage.