Cognosis Citadel — Enterprise AI for Financial Institutions

Tomorrow morning

Watch your best analyst between 8:00 and 11:00 a.m.

She opens the CIM that arrived overnight. She copies EBITDA figures into Excel, one by one. She cross-checks page 47 against appendix C, finds a discrepancy, and rereads both. She hunts through last quarter’s folder for the comp set someone built before.

By 11:00 she has numbers she trusts — and she hasn’t started thinking yet. Three hours of her morning went to reading, copying, and reconciling.

Multiply that morning across every analyst, every deal, every quarter. That’s the tax you’re paying — and it’s the first thing we remove.

The 8-to-11 problem

8:04Opens the overnight CIM. Starts copying EBITDA figures by hand.

9:12Page 47 disagrees with appendix C. Rereads both.

9:58Digs through last quarter’s folders for an old comp set.

11:00Finally has numbers she trusts. Thinking starts now.

With usThe draft was waiting at 8:00 — sourced, reconciled, in your template.

In production

The workflows firms operationalize first.

Real deployments, real deltas. Find your desk below — then ask us to reproduce the number on your own documents.

Private Equity & M&A

Data room → IC memo: 100+ hrs → under 10
CIM → LBO model prep, your template: 5–7 hrs → 15 min
Deal screening against your thesis: 3× more deals covered

Investment Banking

Earnings comps & precedent analysis: same-day, every name
Profiles, teasers & pitch pages: drafted before kickoff
Meeting prep & news runs: assembled overnight

Wealth Management

Source-of-wealth & KYC assembly: days → hours
Client onboarding: checked, nothing retyped
Portfolio commentary: personal, every quarter

Hedge Funds & Asset Mgmt

Earnings call & filing analysis: minutes after transcript
Bull/bear cases: 3× more sources per decision
Market & portfolio briefs: in the inbox at open

Banking & Insurance

Claims assessment throughput: +33%, same team
Contract review: 60 min → 6 per agreement
RFP & DDQ completion: drafts from your own KB

Operations & Reporting

Board packs & investor reporting: assembled & sourced
Recurring reports: write themselves on schedule
Every output: traced to source, audit-ready

Every figure on this page gets re-measured on your documents, against metrics you define, in an eleven-day POC. If a number doesn’t hold at your firm, you find out by day 11 — not month 11.

95%+and the other 5%?

“95% accurate” should raise a question. Here’s our answer.

Every extracted figure carries a link to the exact page it came from. Your analyst doesn’t take the memo on faith — she clicks, checks, and corrects in minutes instead of assembling for hours. Nothing reaches your IC unverified; the platform moves your people from typist to reviewer, and the audit trail comes built in.

The platform

One platform. Four capabilities. Shaped around how your firm already works.

Amplify

AI Workspace

Where the 8-to-11 problem disappears. Chat with any file or data source and produce institutional-grade output — memos, comps, profiles — in your house format, with every claim sourced.

Execute

Financial Agents

Agents that don’t just answer questions — they run the workflow end to end, the way your team runs it: diligence, KYC, screening, monitoring, reporting.

Connect

One Brain for the Whole Institution

Today your firm’s knowledge lives in fragments — deals in the CRM, research in shared drives, client history in inboxes, market data in terminals. Every system you run feeds one secure, governed data lake, so every memo starts with the full picture.Via MCP — the open standard for connecting AI to enterprise systems — plus native connectors. Each system added makes every workflow smarter.

Tailor

Customization Engine

Your templates, your language, your sign-off rules. An intuitive no-code builder for your desks — plus a full API and SDK for your engineers.

Integrations

It plugs into what your firm already runs.

No rip-and-replace, no “new system of record.” The platform reads from the tools your teams live in today — respecting every permission — and delivers finished work back in the formats your firm already uses.

Where your knowledge lives today

DealCloudSalesforceSharePointOutlook BloombergFactSetCapital IQPitchBook DatasiteSnowflakeEDGAR filings…

MCP + native connectors

The operating brain

One governed data lakeyour permissions, your perimeter

Agents run your workflows end to end
Workspace answers with full firm context
Every output traced to its source

In your formats

Where the work lands

Excel — your model templatePowerPoint — your pitch pages Word — your memo formatOutlook & Teams — delivered where you read

CRM & deal management

DCDealCloud

SFSalesforce

DYDynamo

AFAffinity

Documents & data rooms

SPSharePoint & OneDrive

GDGoogle Drive

DSDatasite

ILIntralinks

Market data & research

BBBloomberg

FSFactSet

CIQS&P Capital IQ

PBPitchBook & Preqin

Email, calendar & chat

OLOutlook & Exchange

GMGmail & Google Calendar

TMMicrosoft Teams

SLSlack

Warehouses & infrastructure

SNSnowflake

DBDatabricks

S3Amazon S3

SQPostgres & SQL Server

Where outputs land

XLExcel — in your model template

PPPowerPoint — your pitch pages

WWord & PDF — your memo format

@Delivered by email, Teams, or portal

Run something that isn’t on this list? That’s what MCP is for — the open standard for connecting AI to enterprise systems means a new connector takes days, not quarters. Every connection is read-scoped to your permission model, and nothing leaves your perimeter.

How we deploy

What actually goes into delivering this.

Every enterprise AI deployment involves some version of this work. Most vendors don’t tell you what it is. Here is ours, step by step — dates included.

Day 1

We listen before we demo.

An introductory call about your priorities, your workflows, and your stack. We ask which three workflows consume the most analyst-hours per week — that answer decides everything that follows.

Day 3

We scope the POC on your real documents.

One workflow, your actual files, and success metrics you define — accuracy thresholds, time targets, output format. We test on your documents because a demo on ours would prove nothing.

Day 11

You see measured results, not a pitch.

Side-by-side: the workflow as your team runs it today versus the platform’s output, scored against the metrics from day 3. If the numbers don’t hold, you’ve spent eleven days finding out — not eleven months.

Weeks 3–6

We sit with your analysts and learn the firm.

Our team records how your people actually build a memo — every source, every sanity check, every formatting rule. Then we fine-tune the models to your language, your templates, and your conventions, and connect the first systems to the data lake. This is the hand-in-hand part: your team teaches the platform, our team makes it stick.

Months 2–4

Firm-wide rollout with embedded experts.

Structured training desk by desk, adoption tracked weekly, and continuous benchmarking against ground truth as more systems join the lake. The tuning never stops, because your goals don’t.

Forward-deployed engineering

We hold your hand, build with you, and ship results — until you don’t need us.

Every deployment ships with forward-deployed engineers: finance-fluent builders who sit at your analysts’ desks, run the first workflows with them, and encode every correction into the platform. Software vendors hand you a login. Consultants sell you hours — forever. An FDE’s mandate is the opposite: transfer the capability, then get out of the way.

The handover curve

Your firm’s capability Our hands-on involvement

The curves are the engagement design; the measurements underneath are real — accuracy against your benchmarks, adoption desk by desk, and time-to-self-serve, tracked weekly from day 11. When the lines cross, that’s not us leaving. It’s the deployment working.

Phase 01 · Days 1–11

We build. You judge.

Our engineers run the first workflow on your documents, against metrics you set. You don’t configure anything — your job is to hold the standard.

Phase 02 · Weeks 3–16

We build together.

FDEs at your analysts’ desks: every source, sanity check, and formatting rule gets encoded. Your people make their first changes with our hands still on the wheel.

Phase 03 · Month 4 onward

You build. We’re on call.

Your team ships new workflows in the builder; we review, benchmark, and recede to on-call. The platform keeps learning. So do your people.

Consultancies bill hours, so dependency is the business model. Our engineers are measured on graduation day — the first workflow your team ships without us in the room.

Why Incompleteness

Why firms choose us — and why they stay.

Your people, multiplied — with the numbers to prove it.

An analyst covering three times the pipeline. A partner walking into every meeting already briefed. A memo that took a hundred hours now taking ten — with the saved ninety going to judgment, relationships, and the work that wins mandates. We put a figure on every claim, because the figures are the point.

Fitted to your firm, down to the last workflow.

Workflows, agents, templates, prompts, models, outputs — all of it configures to how your firm actually operates. A memo that comes back in someone else’s format gets rewritten; a tool that fights your process gets abandoned. Fit is what makes adoption stick.

Forward-deployed, measured on your graduation.

Every deployment is a partnership, not a license key. Our forward-deployed engineers embed with your team, tune the models to your institution’s language and objectives — and are measured on how quickly you stop needing them, not on seats sold or hours billed. See the handover curve →

A data lake that compounds.

The platform keeps absorbing new systems and sources into one secure, governed lake — and each connection makes every workflow smarter. That’s why it’s worth more to you in month twelve than month one, and more in year two than year one.

Secure by pedigree.

Our roots are in AI security testing, so the foundations were never an afterthought: end-to-end encryption, granular permissions, full audit trails, and zero training on your data. Your InfoSec team gets the complete picture under NDA — and they’ll like what they find.

SOC 2 ISO 27001 GDPR EU AI Act No training on your data

AI sovereignty

Every firm is about to use AI. Very few will own theirs.

OpenAI, Anthropic, Google — the frontier labs sell the same intelligence to you and to everyone you compete against. A subscription can’t be an edge; whatever a rented model does for you on Monday, it does for the fund across the street on Tuesday. Your edge is the one thing the labs don’t have: your deal history, your templates, your people’s judgment. Sovereignty means that edge compounds inside your walls — instead of leaking into someone else’s product.

Renting intelligence

Same model as your competitors. Identical capabilities, identical outputs, zero differentiation.
Generic by design. It has never read your past deals, doesn’t know your house view, and formats memos like everyone else’s.
Your usage improves their product. The learning accrues to the vendor’s platform, not to your firm.
The relationship is a subscription. Cancel it and nothing remains — no asset, no memory, no moat.

Owning it

Models fine-tuned to your firm — your language, your templates, your investment thesis — inside your security perimeter.
A data lake that is your asset. Every deal, memo, and connection makes your system smarter, not a shared one.
Zero training on your data. Your edge stays yours — contractually, architecturally, verifiably.
An institutional capability that compounds. Worth more in year two than year one, and it belongs to you.

The winners of the last cycle were the firms that became software organizations. The winners of the next will be the firms that become AI organizations — not customers of one.

Here’s the version of your firm this builds.

Your analysts screen three times the deals — and spend their mornings thinking, not retyping.

Your partners walk into every meeting with the full picture: deal history, client context, market backdrop.

Your institution’s knowledge stops living in fragments and starts compounding in one brain.

Your firm owns an AI capability of its own — one your competitors can’t subscribe to.

Eleven days from the first call, you’re looking at measured results on your own documents.