Can Finster AI be deployed single-tenant or in our VPC, and what’s the implementation process/timeline?

Most front-office teams ask the same two questions early: can Finster run in our own environment, and how long will it actually take to be live in production? The short answer: yes, Finster can be deployed single-tenant or inside your VPC, and implementation is measured in days to low-single-digit weeks, not quarters.

Below is a clear breakdown of deployment options, technical architecture, and a realistic implementation timeline so your risk, security, and front-office stakeholders are aligned from day one.

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Deployment Models: SaaS, Single-Tenant, and VPC

Finster is built to meet banks, asset managers, and private credit firms where they are on security and infrastructure. There are three main deployment options:

1. Standard SaaS (Fastest time-to-value)

What it is

• Multi-tenant SaaS with strict logical isolation and private upload tenants.
• No training on your data—ever.
• Encryption at rest and in transit, with SOC 2-compliant controls.

When it’s a fit

• You want value on Day 1 with minimal integration work.
• Your security team is comfortable with enterprise-grade SaaS for research workflows.
• You’re testing or rolling out to a specific team (e.g., sector coverage group, credit desk) before scaling firmwide.

2. Single-Tenant Deployment (Dedicated environment)

What it is

• A dedicated, containerized instance of Finster.
• No infrastructure is shared with other clients.
• Option to “bring your own LLM” via your own API keys; Finster is LLM-agnostic.

When it’s a fit

• You need hard tenancy boundaries for regulatory, client, or internal policy reasons.
• You want tighter control over data residency, performance isolation, or integration standards.
• You’re planning a broad, multi-desk rollout and want a clearly ring-fenced environment.

Why teams choose it

• Clearer story for risk and compliance: your instance, your tenancy, your logs.
• Easier to align with internal standards around data segregation.
• Simplifies conversations with clients who demand demonstrable isolation.

3. Containerized VPC Deployment (Your cloud, your controls)

What it is

• Finster deployed as a containerized stack within your own cloud environment:
  • Supported clouds: AWS, GCP, Azure.
  • Your VPC, your IAM, your network controls.
• The only required external communication is to:
  • FactSet APIs and other licensed data providers.
  • Any other external datasets you choose to connect.

When it’s a fit

• You operate in highly regulated environments where data must stay inside your perimeter.
• You already have strong internal cloud standards (Zero Trust, strict IAM) and want Finster to sit inside that fabric.
• You want maximum control over network paths, observability, and change management.

Why teams choose it

• Aligns with “cloud-first but controlled” architectures.
• Simplifies sign-off from internal security architecture teams.
• Enables tighter integration with internal data lakes, document stores, and monitoring stacks.

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Security and Data Handling Across All Models

Regardless of deployment model, a few principles never change:

• No training on your data
  Finster will never train AI systems on your proprietary data or user interactions.

• Enterprise-grade security posture

  • SOC 2 compliance.
  • Encryption at rest and in transit.
  • Zero Trust-aligned approach with least-privilege access.
  • Audit logging for user activity and system actions.

• Permission-aware retrieval

  • Role-based access control (RBAC).
  • SSO via SAML and SCIM provisioning so entitlements and offboarding are managed centrally.
  • Optional private deployments (single-tenant or VPC) with no shared infrastructure.

• Safe-fail behavior
  When data is missing or ambiguous, Finster returns “I don’t know” / “no answer” rather than guessing. That’s non-negotiable in a world where a single hallucinated number can’t survive compliance review.

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Implementation Process: From Initial Call to Live Workflows

The implementation process is designed to be predictable and light-touch on your side—no “forward deployed engineering” dependency, no year-long project.

Below is the typical sequence for single-tenant and VPC deployments; SaaS follows the same stages but compresses timelines.

Step 1: Discovery and Requirements (Week 0)

Objectives

• Align on workflows and constraints, not just features:
  • Investment banking: earnings updates, comps, CIM prep, monitoring packs.
  • Asset management: idea generation, coverage maintenance, earnings season workflows.
  • Private credit: underwriting, ongoing monitoring, covenant/waiver packs.
• Capture security and architecture requirements:
  • Deployment model (SaaS vs single-tenant vs VPC).
  • Data residency and regulatory constraints.
  • Existing identity providers and SSO setup.
  • Required integrations (FactSet, internal SharePoint/Data Room, data lake connections).

Outputs

• Agreed deployment model and environment (e.g., AWS VPC in region X).
• Integration plan and initial success criteria (“what good looks like” in 4–8 weeks).

Step 2: Environment Provisioning (Week 1–2)

Single-Tenant

• Finster provisions a dedicated containerized environment.
• Hard tenancy boundaries configured at the infrastructure level:
  • Separate databases and storage.
  • Separate compute resources.
  • Dedicated logging and monitoring.

VPC Deployment

• Finster provides:
  • Architecture diagram and reference deployment templates (e.g., Terraform / Helm).
  • Network and firewall requirements (egress to FactSet and other data APIs).
• Your infra team:
  • Sets up VPC, subnets, security groups, and IAM roles per architecture.
  • Establishes connectivity to any required internal systems (e.g., SSO, document stores).
• Joint validation of:
  • Network connectivity.
  • DNS / endpoint configuration.
  • Observability hooks (logs/metrics into your stack if required).

Typical effort on your side

• A few days of part-time work from security/infra teams to check boxes and approve patterns.
• No fundamental re-architecture or bespoke engineering.

Step 3: Identity, Access, and Compliance Alignment (Week 1–3, in parallel)

What gets done

• SSO integration

  • SAML SSO configured with your identity provider (Okta, Azure AD, etc.).
  • Group-to-role mapping defined (e.g., IB_Equity_Research → “Research Power User”).

• SCIM and provisioning

  • Optional SCIM integration for automated user lifecycle management.
  • Entitlements and least-privilege roles aligned with your internal access model.

• Compliance and audit trail alignment

  • Review logging scope (user actions, queries, document access).
  • Confirm export/retention policies where relevant.
  • Make clear how MNPI handling is controlled and evidenced.

Outcome

• A permission-aware, audit-ready environment that meets risk and compliance expectations before front-office users ever log in.

Step 4: Data Sources and Connectors (Week 2–4)

This is where Finster stops being “an AI platform” and starts being your AI Analyst.

External and licensed data

• Native connectors and entitlements alignment for:
  • FactSet, Morningstar, PitchBook, Crunchbase.
  • Third Bridge expert interviews, Preqin private markets data.
  • MT Newswires real-time headlines.
• Primary sources:
  • SEC filings, company sites, and investor relations materials ingested into a unified pipeline.

Internal documents

• Connect to internal repositories:
  • SharePoint, internal research portals, data rooms, knowledge bases.
  • Upload workflows for presentations, models exports, memos, and underwriting packs.
• Configure permissions so:
  • A user only sees and retrieves from documents they’re entitled to.
  • Every citation respects your existing access model.

Outcome

• A live, permission-aware knowledge layer that brings external and internal sources together with granular citations down to the sentence or table cell.

Step 5: Workflow Configuration and Finster Tasks (Week 3–5)

This is where front-office impact starts to show.

Workflow templates (“Finster Tasks”)

• Configure and customize Tasks for common workflows:
  • Earnings analysis and post-call summaries.
  • Peer comps and benchmarking.
  • Sector / theme primers and deep dives.
  • Underwriting memos and monitoring packs.
  • Portfolio and coverage monitoring with scheduled or triggered updates.

Decision points

• What should be scheduled vs on-demand?
  Example: automatic monitoring packs each quarter; on-demand deep dives for live deals.

• What formats do you need by default?

  • Client-ready tables (valuation, comps, KPI tracking).
  • Draft slides or memos for quick editing.
  • Export options to your standard decks or templates.

Outcome

• End-to-end workflows automated from ingestion → search → synthesis → client-ready deliverables, with every number cited back to source.

Step 6: Pilot, Training, and Scale-Up (Week 4–8)

Pilot

• Start with a focused group:
  • A specific coverage or sector team.
  • A single private credit desk.
  • A subset of portfolio managers and analysts.
• Measure against clear KPIs:
  • Time saved per earnings cycle.
  • Turnaround time for monitoring packs.
  • Number of client-ready outputs drafted per week.

Training and enablement

• Short, workflow-specific sessions:
  • “How to run an earnings update in 10 minutes.”
  • “How to build comps and track revisions with citations.”
  • “How to use Finster Tasks for underwriting and monitoring.”

Scale-up

• Expand to other desks/regions once:
  • Security and compliance sign-offs are done.
  • Pilot teams are consistently using Finster in live workflows.
  • Change management is minimal because users see the benefit in deal speed and auditability.

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Realistic Timeline Expectations

Timelines vary by internal process, but patterns are clear:

• Standard SaaS

  • Technical setup: days.
  • SSO + basic workflows: ~1–2 weeks.
  • Pilot in production: within the first month.

• Single-Tenant

  • Environment provisioning: ~1–2 weeks.
  • SSO + data sources + Tasks: ~2–4 weeks total.
  • Pilot in production: typically weeks, not months, from contract.

• VPC Deployment

  • Environment setup in your cloud: ~2–3 weeks (depending on infra approvals).
  • SSO, data connectors, workflows: typically in parallel, total ~3–6 weeks.
  • Pilot in production: often within one quarter, frequently faster when infra teams are aligned early.

The key variable is not technology; it’s internal decision velocity—security reviews, IAM approvals, and data governance sign-off. The underlying stack is designed to be deployable and repeatable, without an army of engineers.

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How to Decide Between SaaS, Single-Tenant, and VPC

When comparing options, most institutions use three lenses: risk posture, integration depth, and speed to impact.

• Choose SaaS if:

  • You want the fastest route to value.
  • You’re comfortable with enterprise SaaS plus private upload tenants.
  • You’re starting with a scoped deployment and expanding as you prove impact.

• Choose Single-Tenant if:

  • You want stricter isolation but don’t need to host in your own cloud.
  • You want optional control over the LLM (BYO API keys).
  • You want a simple, clean story for regulators and clients about environment boundaries.

• Choose VPC if:

  • Your policies require workloads to run inside your own cloud perimeter.
  • You want to plug Finster directly into internal data lakes, research repositories, or monitoring systems.
  • You want maximum control over network, IAM, and observability.

In all three cases, the core benefits are the same: every insight cited, every source auditable, no training on your data, and a system that will say “I don’t know” rather than guess.

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If you want to see what a single-tenant or VPC deployment would look like in your environment—including architecture diagrams, security controls, and a concrete 30–60 day rollout plan—the next step is straightforward.

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