Adept Scientific | For Manufacturers

The black box of lab execution, revealed.

Whether you manufacture reagent kits, analytical instruments, or lab automation systems, you face a common challenge: once your product ships, you lose visibility into how it's actually executed. Adept bridges the gap between your product teams and the scientists at the bench.

Every Run

Every Product

Every Lab

Every Insight

How it works

A seamless data pipeline from the scientist's benchtop directly to your product team's dashboard.

01

Real-World Data

Capture at the bench.

Our zero-friction mobile copilot guides scientists through your protocols step-by-step. As they work, the app passively captures real-time execution data, dwell times, and customer voice queries ("Why is this cloudy?").

✓ Exact timing per step
✓ Voice-recorded deviations and pauses
✓ Step completion rate

Adept mobile app: DNA Library Prep protocol screen with past runs

Explore the Live Dashboard 6 manufacturer personas · sample data · opens in a new tab View Dashboards

02

Proactive Insights

Analyze in the platform.

Field data is aggregated and anonymized into interactive dashboards. Instantly spot step-level bottlenecks, track lot-to-lot quality variance, and monitor early-warning churn signatures across accounts.

✓ Protocol Success Rate tracking
✓ Weekly active experiments by SKU
✓ Competitor switching signals

See a live dashboard

Best viewed full-screen on a larger display.

03

Real Outcomes

One platform. Many outcomes.

Adept empowers every role from customer success to senior leadership.

Stop guessing what goes wrong after the kit leaves your warehouse. Use hard telemetry to proactively update User Guides, deploy targeted field alerts, and resolve support tickets faster.

In practice: a single flagged reagent lot shows up automatically in both Support's ticket queue and Quality's watchlist — the same signal, seen by both teams, without anyone connecting the dots by hand.

Explore all six dashboards

Customer Success One health score — success rate, deviations, and query volume — flags which accounts need a call today.

Technical Support A ranked triage queue traces this week's ticket spike straight to the lot causing it.

Product A step-by-step confusion heatmap shows exactly which page to fix next in the user guide.

Quality Lot-level success rates flag a failing lot for quarantine before it becomes a complaint.

Marketing Adoption curves show which assay is taking off months before published research confirms it.

The problems we hear again and again.

Real conversations with life science manufacturers. Hover over a card to see what we heard.

01 · Execution Ambiguity

How do you know whether a failed result came from the product or from execution?

Hover to see what we heard

“If we assume they did everything perfectly ... then yeah, the results are the results. But boy, do we really believe that?”

— Sr. Dir. of Application Support, Life Sciences Manufacturer

02 · Bad Support Data

How do product teams get visibility into what’s actually happening at the bench today?

Hover to see what we heard

“Product managers don't get reliable data from support tickets.”

— Product Manager, Tier 1 Life Sciences Manufacturer

03 · Documentation Isn't Enough

Why are customers still asking questions that are already answered in the protocol?

Hover to see what we heard

“Not a single customer has ever read their user guide start to finish.”

— Technical Support Lead, NGS Reagent Manufacturer

04 · Silent Churn

How often do customers try your product and disappear without ever asking for help?

Hover to see what we heard

“We’re sending out free samples and it’s like, ‘Have you tested it?’”

— General Manager, Life Sciences Reagent Manufacturer

05 · Long Optimization Cycles

How many weeks or months are troubleshooting and optimization cycles adding to adoption?

Hover to see what we heard

“It could be months or it could be weeks.”

— Commercial Lead, Reagent Kit Manufacturer

06 · Support Burden

How much of your support burden comes from users who aren’t experts?

Hover to see what we heard

“Half our customers are not experts, and those are the ones that require the most extensive support.”

— Sr. Dir. of Application Support, Life Sciences Manufacturer

What scientists say

Built for the bench, by scientists who've been there

Real feedback from our early access program.

It is like having a lab notebook without having to write and type one, and I very much like that.

— Early Access Scientist

I love the ghost of the previous and future step display — giving a reminder of what was just done and what to look forward to.

— Early Access Scientist

I particularly love the fact that it does the calculations for me.

— Early Access Scientist

Adept offers a solution that cuts the planning time in the lab substantially. For a new kit, or even a kit I've been using, interacting with the protocol and creating documentation in real time changes the game.

— Scientist, Private Biomedical Research Org

I think having an AI trained to the level of a senior scientist on a specific workflow and its underlying molecular biology would be a real asset — a force multiplier — for a team, assisting a technician or research assistant every time they run the workflow on a plate of samples.

— Scientist, NGS Company

What immediately caught my eye was your first sentence: 'keep your gloves on'. Had me envisioning a world where a trained AI is there to consult with when I, or a teammate, has gloves on, a pipette in hand, and something unexpected happens. I've spent the last 15 years managing teams and executing complex NGS protocols on large cohorts of samples myself — I've had numerous moments where a tech would have to leave the lab, come find me, and ask a question that pauses the whole workflow.

— Scientist, NGS Company

I loved trying out the app; it was nice that it was self-paced. Having it tells you exactly what you need, like the temp based on bp, is super cool. That would save me time and brain power. I think I would use this every time or close to it, especially for a more complicated procedure.

— PhD Candidate, Biology

I think having an AI trained to the level of a senior scientist on a specific workflow and its underlying molecular biology would be a real asset — a force multiplier — for a team, assisting a technician or research assistant every time they run the workflow on a plate of samples.

— Scientist, NGS Company

What immediately caught my eye was your first sentence: 'keep your gloves on'. Had me envisioning a world where a trained AI is there to consult with when I, or a teammate, has gloves on, a pipette in hand, and something unexpected happens. I've spent the last 15 years managing teams and executing complex NGS protocols on large cohorts of samples myself — I've had numerous moments where a tech would have to leave the lab, come find me, and ask a question that pauses the whole workflow.

— Scientist, NGS Company

I loved trying out the app; it was nice that it was self-paced. Having it tells you exactly what you need, like the temp based on bp, is super cool. That would save me time and brain power. I think I would use this every time or close to it, especially for a more complicated procedure.

— PhD Candidate, Biology

Why partner with Adept?

Make data-driven product improvements based on trustworthy real-world execution data collected at scale, while providing white-glove, real-time product support to every customer.

Today's Reality

✕ Support tickets are fragmented and incomplete.
✕ Field visits are infrequent, meaning you miss the majority of what actually happens at the bench.
✕ Feature priorities are based on best guesses rather than hard utilization data.
✕ There's no way to compare performance or support burden across SKUs or customer segments.
✕ You have no early warning system for accounts that are quietly at risk.
✕ Support burden keeps climbing even as your documentation gets more thorough.
✕ Slow root-cause diagnosis delays adoption and time-to-value on new SKUs.

With Adept

✓ Structured failure data: Every protocol step generates actionable field data.
✓ Real-time signal: Surface product issues as they occur, not weeks or months later.
✓ Faster iteration: Go from months of guesswork to weeks of data-driven improvements.
✓ Confidence at scale: Consistent, automated customer support across your portfolio that scales.
✓ Accelerate R&D: Real-world data means every experiment informs the next product cycle.
✓ Competitive intelligence: Aggregated, anonymized telemetry surfaces workflow failure patterns across vendors.

Cost Savings Calculator

Support costs scale with every product you ship.

See your Year 1 impact.

Tune the assumptions below to model how much Adept could save your support organization in year one.

Your Portfolio

Cost to resolve a support ticket $500

# of tickets per SKU annually 500

# of SKUs in portfolio 20

% of tickets deflected by Adept 90%

Your Year 1 Impact

Total support cost today $5,000,000

Total cost with Adept $505,000

Net Year 1 savings $4,495,000

Cost reduction 90%

Get a Custom ROI Analysis

Today — Without Adept

Annual tickets across portfolio10,000

Total annual support cost$5,000,000

With Adept

Tickets deflected9,000

Residual tickets handled by your team1,000

Residual support cost$500,000

Adept pilot investment$5,000

Total cost with Adept$505,000

Estimates only, based on the figures you enter above. Assumes a flat $5,000 Adept pilot investment covering setup for your initial product family. Actual savings depend on your existing support cost structure and deployment scope — talk to us for a tailored analysis.

Enterprise-grade privacy, security, and data protection.

All data is encrypted in transit and at rest using industry-leading standards. Each deployment is strongly isolated with role-based access and MFA for privileged users — nothing is shared across customers, and nothing is used to train third-party models.

Questions? Answers.

Everything a commercial or product leader wants to know before piloting Adept.

How does Adept integrate with our existing kits or instruments?

Adept is embedded as a branded field support agent alongside your protocol — there's no re-engineering of your kit or instrument required. Scientists access step-by-step, voice-guided instructions through a lightweight companion app tied to your SKU.

What happens to our proprietary usage data?

Your data stays yours. Each deployment gets a strongly isolated, siloed knowledge base and analytics that are never shared across customers, encrypted in transit and at rest, with role-based access and MFA for privileged users. We don't use your documentation or data to train third-party models — transcripts and usage stats are used only to deliver and improve your own deployment. At contract end, your data is returned or deleted per the agreed retention window, and data governance is worked out before any agreement is signed.

How is this different from our field application scientists or a tool like Zendesk?

Field application scientist teams provide expert support but don't scale and capture little structured data. Generic support platforms handle tickets, not multi-step protocol execution. Adept guides the protocol itself, in real time, and turns every run into structured, SKU-level intelligence — something neither approach produces today.

What does a pilot involve, and how long does setup take?

Pilots are scoped around a single flagship product family so you can validate value quickly. Since there's no engineering lift required on your side, most manufacturers are live within weeks.

What does Adept cost?

Pricing is structured per product family, so you only pay for the SKUs where support burden is highest. Use the calculator above to estimate your potential savings, then talk to us for a quote tailored to your portfolio.

Which manufacturers is Adept built for?

Adept is built for manufacturers selling complex, workflow-intensive products — including NGS reagent kits, analytical instruments, and liquid handling automation — where protocol execution is high-stakes and support burden is acute.

Kristina Fontanez, PhD, Founder and CEO of Adept

Founder-led. Built by scientists.

Adept is led by Kristina Fontanez, PhD, a repeat founder who co-invented the single-cell technology powering Illumina’s Billion Cell Atlas. She previously co-founded Fluent BioSciences, acquired by Illumina for $85M in 2024.

After 12+ years building molecular tools, she's now solving the real-time support bottleneck for genomics and life science products at scale.

She's building Adept alongside Drew Bryant, PhD (Head of Software Engineering — ex-Google, ex-Amazon) and Jason Callina (CTO — ex-Woebot Health), bringing 30+ years of combined experience shipping production software and scientific AI/ML.