Savant Labs

AI Automation Platform for Critical Data Workflows

Savant Labs empowers analysts to expedite answers from modern data sources and modern SaaS applications with drag-and-drop no-code, low-code analytics automation and generative AI. The analytics automation is visualized in an intuitive workflow that combines dataflows and analytics flows and uniquely combines analytics bots. Organizations can leverage Savant's pre-build analytics automation apps a

nd solution workflows or build their own while also leveraging the power of AI for further automation.

08/27/2026

The tax landscape is evolving rather quickly. Rules are tightening, reporting is moving closer to real time, and expectations keep climbing.

Legacy tax models cannot absorb this pressure. Spreadsheet handoffs break lineage at every touch. Fragmented tax code libraries mean identical transactions resolve differently across systems. Evidence assembled weeks after the fact arrives too late to matter.

In this environment, seven key questions will determine how your tax function performs in 2026 and beyond.

We built The 2026 Tax Leader Decision Map around the seven questions that actually change outcomes, from external forces and operating model design through funding modernization on a flat budget and governing agentic AI in production. Each one comes with concrete next steps you can put on a 90-day plan.

Are you on the right path?

https://savantlabs.io/ebook/2026-tax-leader-decision-map/

08/25/2026

373 Chief Audit Executives told the IIA they need more resources.

The 2026 Pulse numbers are blunt. Those reporting insufficient funding climbed from 22% to 30% in a single year. 18% of functions cut staff, matching COVID-era levels.

At the same time, scope went the other direction. 86% of CAEs now own at least one area outside internal audit. 47% run fraud investigations. 34% own enterprise risk management. In public companies, 80% carry the SOX program.

What the Pulse report never counts is the operational overhead underneath it all. Pulling extracts, normalizing formats, chasing documentation, reconciling the same population across three systems before anyone can test a single control… That work consumes real capacity every quarter.

Hiring is the expensive, temporary answer. The more effective move is automating these processes as governed workflows with deterministic logic and full lineage, built to survive review rather than explain itself afterward.

The capacity is already sitting in your function. It’s just buried in manual data work.

Read the full breakdown: https://savantlabs.io/blog/internal-audit-resource-gap-2026/

08/18/2026

🏆 Savant Racks Up Nine Wins in G2's Summer 2026 Reports

Savant earned Momentum Leader, High Performer, and Easiest To Do Business With badges across multiple categories in G2’s Summer 2026 reports.

The recognition validates what we’re building for finance teams: AI automation they can trust with critical work.

With Savant, finance teams can bring AI into close, tax, and reporting workflows without giving up human review, control, or auditability.

Fast AI is everywhere. Auditable AI is the standard that matters.

See what Savant can do for your finance workflows → https://savantlabs.io/book-a-demo/

08/13/2026

Teams that aren’t subject to regulatory audits can ship an AI draft that's 90% right and fix the rest later. A controller cannot file a number that's 90% right. That asymmetry is why AI risk in finance looks nothing like AI risk anywhere else.

The failure modes that matter don't show up in a polished demo. They surface six months later in an audit, a restatement, or a budget review.

Leading models still hallucinate at 9-14% rates, and those climb on long documents like financial filings. LLMs can return two different answers with different reasoning for the same question. And "the model decided" doesn't hold up as an audit trail when someone asks how you got the number.

There's more than meets the eye when it comes to AI in finance. Here’s a breakdown of the five biggest blind spots and what to do about them: https://savantlabs.io/blog/ai-blind-spots-finance-leaders/

08/10/2026

Tomorrow – The governance conversation about AI in finance, with an auditor (Corey Merrill, Managing Director, BDO), CFO (Christine Gu, CFO, Clarify Health Solutions), and AI automation leader (Chitrang Shah, CEO & Founder, Savant Labs) in the room.

Three things you'll walk away with:

1️⃣ A clear line between where AI is genuinely useful today and where it fails a regulated workflow
2️⃣ The vendor evaluation questions that matter: change management, versioning, testability, segregation of duties, and more
3️⃣ What a defensible AI risk assessment actually covers

Live Q&A at the end. Bring the questions you haven't been able to get a straight answer on.

How CFOs and Controllers Deploy AI That Survives an Audit

🗓️ Tuesday, August 11, 1 PM CST ⏰ 60 minutes ✅ CPE credit eligible

Registering also gets you the recording, so sign up even if the time doesn't work for you: https://buff.ly/2JnNHra

08/06/2026

Ask enterprise tax teams where their time goes, and you'll hear about the same handful of tasks every cycle.

Reconciling book-vs-tax depreciation. Rebuilding apportionment workbooks tab by tab. Looking up treaty rates one payment at a time. Quantifying R&D credits before anything can be filed.

The good news is that this work is rules-based. Pull the data, normalize it, calculate, reconcile, package the evidence. That pattern automates well.

Our latest guide walks through five of these workflows, what each one costs manually, and a five-day plan to stand them up.

SWIPE THROUGH for the breakdown, then get the full guide: https://savantlabs.io/ebook/tax-workflows-you-can-automate-with-ai/

08/05/2026

Finance teams are pointing Claude, ChatGPT, and Copilot at real work. The output looks great, but it isn’t audit-ready.

Consider what an ungoverned AI agent actually does inside a finance workflow. It drafts the journal entry and assesses whether the entry is correct. It builds the reconciliation and decides the reconciliation is complete. It can adjust thresholds and skip validation steps with no change-management gate. AI is both maker and checker, and that’s a control disaster.

Our Co-Founder and Head of Product, Matt Mesher, lays out the five questions your auditor is about to ask, and three things you can do now to close the gap: https://savantlabs.io/blog/finance-ai-audit-readiness/

08/04/2026

What should AI in finance look like for an auditor to sign off on it?

Tools like Claude and ChatGPT aren’t built for the evidence, reproducibility, and control design SOX requires.

Looking to automate finance workflows without increasing risk? Our upcoming webinar with Controllers Council is for you. Here's what it covers:

👉️ Where AI is genuinely useful right now. Christine Gu (CFO, Clarify Health Solutions) and Corey Merrill (Managing Director, BDO) on what controllers and finance teams are doing successfully with tools like Claude and ChatGPT today.

👉️ Where AI breaks down. Corey explains what he's seen flagged in audits when AI output was relied on without controls.

👉️ The missing layer. Chitrang Shah (CEO & Founder, Savant Labs) goes over the control layer that’s needed to make AI in finance truly reliable, defensible, and audit-ready.

👉️ How to evaluate a vendor. Corey discusses the questions to ask before trusting AI inside a control environment, and understanding whether the vendor is managing the associated risks or handing those back to you.

How CFOs and Controllers Deploy AI That Survives an Audit
🗓️ Tuesday, August 11, 1 PM CST ⏰ 60 minutes ✅ CPE credit eligible

Get a clear answer on what a defensible AI risk assessment actually looks like: https://register.gotowebinar.com/register/1374976030865868117?source=savant

08/03/2026

A warm welcome to Brett Jenkins, joining Savant as Sales Director.

Really glad to have him on the team, and grateful for the customers and partners he'll get to work with along the way.

07/29/2026

We tested Claude Cowork against the kinds of work enterprises finance teams actually run.

The reasoning was genuinely impressive. Claude understood business intent, interpreted messy inputs, and produced strong first-pass outputs with minimal instruction. But reasoning is only one layer.

When we looked at planning and ex*****on, the gaps became clear. The "plan" was often generated code, not a workflow a team could inspect or maintain. Large files caused breakdowns, outputs still required significant human validation, and connectivity to enterprise systems of record was limited.

AI on its own falls short. It needs a control layer to close the gap between a good answer and a governed, repeatable workflow your team can run every month.

Our CEO, Chitrang Shah, breaks down the full evaluation: https://buff.ly/SkJgGIl

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