New order, copied by hand
The same fields typed into three systems again.
Forward-Deployed AI Engineering
Build Capacity to Grow. Become AI Native.
We embed with mid-market and enterprise teams to build production AI systems, agents and internal tools around the workflows constraining growth.
The Problem
Your Team Is Carrying Work an AI System Should Handle
Critical workflows still depend on people moving data between systems and manually directing AI.
Today
More people to keep growth moving
Each tool helps with one task. The team holds the process together.
The new way
AI agents to expand team capacity
Shared business context. People step in where judgment is needed.
Business workflows running
AI Systems operating within guardrails
- ↳Order intake validated3h saved
- ↳Lead researched and scored2h saved
- ↳Context written to the record1h saved
- ↳Quote assembled and checked4h saved
- ↳Draft prepared for review3h saved
- ↳Exception flagged for a person1h saved
- ↳Numbers consolidated5h saved
- ↳CRM updated2h saved
- ↳Stock checked against the order1h saved
- ↳Handoff cleared2h saved
- ↳Order intake validated3h saved
- ↳Lead researched and scored2h saved
- ↳Context written to the record1h saved
- ↳Quote assembled and checked4h saved
- ↳Draft prepared for review3h saved
- ↳Exception flagged for a person1h saved
- ↳Numbers consolidated5h saved
- ↳CRM updated2h saved
- ↳Stock checked against the order1h saved
- ↳Handoff cleared2h saved
Same team. More capacity.
Your bottlenecks tell us what to build first.
Solutions
What AI Systems Change Across Your Business
The repeatable work moves to AI systems. The judgment stays with your team. Different work in every department, same shift.
Content and ad creatives move at the speed of the market
Today: content and ad creatives can't keep pace.
What improves
- time from signal to published asset
- assets and creatives shipped per cycle
Every campaign teaches the next one
Today: test results live in a deck nobody reopens.
We build the system that captures what worked, learns from every campaign, and informs what comes next.
…and 50+ other ways to remove bottlenecks like these.
Personalization that knows more than a first name
Today: everyone gets the same message.
What the system handles
- Segment and personalize from behavior and account context · revenue per segment
- Assemble account-specific pages and outreach from the record · engaged accounts per campaign
Buyer signals become briefs, not backlog
Today: they sit unread across reviews, tickets and calls.
What improvestime from signal to published assetcost per qualified response
What's your biggest Marketing bottleneck?
Bring the workflow costing you the most. We'll map the bottleneck and show you what the AI system could look like.
Book a working sessionFree. 30 minutes. Clear system concept.
Every good lead gets worked the day it lands
Today: they wait on research, routing, and qualification.
What improves
- time to first qualified touch
- leads worked per rep
What wins deals changes how you sell
Today: every rep learns the same objections separately.
We build the system that captures what actually moved deals and puts it into the next conversation.
…and 50+ other ways to remove bottlenecks like these.
Outreach and proposals that know the account
Today: they stay generic because personalizing takes too long.
What the system handles
- Research accounts and carry the context into the CRM before the first call · reply rate per sequence
- Draft proposals and quotes from the account record and approved terms · time from request to quote
What's said on calls reaches the forecast
Today: it stays buried in someone's notes.
What improvesforecast accuracytime from call to updated record
What's your biggest Sales bottleneck?
Bring the workflow costing you the most. We'll map the bottleneck and show you what the AI system could look like.
Book a working sessionFree. 30 minutes. Clear system concept.
Reporting stops costing you a week of cleanup
Today: every report starts with fixing the data.
What improves
- hours to a trusted number
- records corrected per week
The rules hold instead of drifting
Today: someone fixes routing, hygiene or a report and it drifts again.
We build the system that holds the rules continuously instead of in a cleanup sprint.
…and 50+ other ways to remove bottlenecks like these.
Context survives the handoff
Today: it gets lost between marketing, sales, onboarding and renewal.
What the system handles
- Carry account context across every stage of the lifecycle · time to full context at handoff
- Flag accounts where ownership or the next step is unclear · deals stalled at handoff
A pipeline number the room believes
Today: every source gives a different answer.
What improvesforecast accuracytime to a trusted number
What's your biggest RevOps bottleneck?
Bring the workflow costing you the most. We'll map the bottleneck and show you what the AI system could look like.
Book a working sessionFree. 30 minutes. Clear system concept.
Volume rises without the copying and chasing
Today: more orders, more hands on each one.
What improves
- orders handled per person
- time from order to confirmed
Exceptions get solved once
Today: whoever's on shift works out the unusual order again.
We build the system that recognizes the pattern, applies the rule and escalates only what's genuinely new.
…and 50+ other ways to remove bottlenecks like these.
Quality checks survive peak volume
Today: the first thing skipped when volume rises.
What the system handles
- Validate orders, documents and requests before they enter the workflow · error rate at intake
- Catch mismatches against stock, pricing and terms at the point of entry · rework per hundred orders
Stock and fulfilment data arrives before the decision
Today: you promise the order, then find out what's in stock.
What improvestime to a reliable stock picturelate or short shipments
What's your biggest Operations bottleneck?
Bring the workflow costing you the most. We'll map the bottleneck and show you what the AI system could look like.
Book a working sessionFree. 30 minutes. Clear system concept.
The month's numbers, early enough to change it
Today: they arrive when the month is half gone.
What improves
- days to close
- hours spent reconciling
Never rebuild the same analysis twice
Today: every close rebuilds it from scratch.
We build the system that carries the logic forward, so the close gets shorter instead of longer.
…and 50+ other ways to remove bottlenecks like these.
Trusted numbers before decisions are made
Today: decisions made on figures nobody verified.
What the system handles
- Check figures against source systems before they reach a decision · exceptions caught before sign-off
- Explain variances with the underlying detail attached · time to answer a finance question
Margin signals arrive before the money is committed
Today: margin shows up at close, a month after the spend.
What improvestime to a current margin viewspend caught before commitment
What's your biggest Finance bottleneck?
Bring the workflow costing you the most. We'll map the bottleneck and show you what the AI system could look like.
Book a working sessionFree. 30 minutes. Clear system concept.
Case studies
In Production, Not in a Demo
AI systems built around real operating constraints.
84%
of prescriptions approved by AI
Featured AI workflow
Prescriptions → restocking
A prescription becomes a restock order
AI reads and validates incoming prescriptions, routes anything uncertain to a person, and projects the demand inside them forward into forecast-led purchasing.
- Before:
- Scripts processed by hand, purchasing blind to demand
- System:
- One workflow from incoming document to forecast-led purchase order
- Safeguard:
- Low-confidence scripts escalate to a person
“We have worked with Revensi for many years. In that time they have made vast improvements to how our business runs, and they are great people to work with. We highly recommend them.”
Delivered for 120+ companies
Approach
Find the Bottleneck. Build the System. Go Live in Four Weeks.
We start with the growth constraint and learn how the work really happens, including the exceptions and judgment calls. Then we build the system around them.
01
Week 1
Map your key bottlenecks
Capture every handoff, exception and judgment call in the workflow we're changing.
02
Week 2
Design the AI systems
Design the context, guardrails and workflows behind the system.
03
Week 3
Embed into operations
Connect the system to your existing tools and test it against real scenarios.
04
Week 4
Launch into production
Go live and measure the impact.
Book a working session
Free. 30 minutes. Clear system concept.
Engagements
Two Weeks to a Roadmap. Four Weeks to Production.
Begin with the roadmap or go straight to implementation. From there, we expand the systems creating measurable impact.
- Recommended starting point
2 weeks
AI Opportunity Roadmap
Define the right opportunity
We trace how work moves, find where capacity is being lost and decide what is worth building.
Starting at$7,500
Credited in full to your implementation.
What's included
- Interviews with the people closest to the work
- A map of the current process and handoffs
- Data and access requirements
- Commercial case and delivery risks
- Recommended scope and measures of success
What you get
A clear, implementation-ready roadmap showing where to invest first and what not to build.
4 weeks
AI Implementation Sprint
Build and launch in four weeks
We turn the biggest bottlenecks into AI systems built around the tools your team already uses.
What's included
- Workflow redesign and operating requirements
- Custom AI systems, integrations and permissions
- Evaluation against agreed examples and criteria
- Human approval and escalation boundaries
- Rollout, documentation and adoption tracking
What you get
Working AI systems handling real work, with the necessary controls and measured impact.
Ongoing
Embedded AI Engineering
Expand AI across your business
We expand successful deployments across teams and keep them reliable as adoption grows.
What's included
- Sequenced roadmap across connected workflows
- Shared context, data and integration layer
- Reusable evaluation and control standards
- Monitoring, optimization and adjustments
- Continuous bottleneck assessment
What you get
AI embedded in day-to-day operations, with the foundations to expand across your business.
Built to Fit, Hold Up and Stay Yours
Technology
The Intelligence Layers Behind Our AI Systems
We combine business context, workflow knowledge and continuous evaluation to build AI systems that perform reliably in the real world.
One context, every signal
refreshed 14 min ago · 35 sources
Context layers
Market
Category shifts, pricing moves, new entrants
Competitors
9 tracked · positioning and packaging deltas
Customers
12.4k accounts · buying history and open threads
Product
Capabilities, configurations, limits, roadmap
Internal
Playbooks, pricing policy, past decisions
Decision-ready signals
Three enterprise renewals are drifting
Act this weeksupport volume up 40% · exec sponsor left in two
read from
A new objection is landing in late-stage calls
Brief salespriced against a bundled suite · 11 mentions, 3 weeks
read from
Buyers changed the words they search on
Draftingagent evaluation, not AI pilot · 2.4x since May
read from
Connected layers of business and market context
Customer, product, market, competitor and internal knowledge made available across workflows.
Decision-ready signals, not raw data
Raw data becomes actionable context, exceptions and priorities that AI systems can reason about.
Context that keeps improving over time
Feedback, outcomes and human decisions continuously strengthen what the whole system knows.
How we compare
Choose the Right Way to Embed AI Into Your Business
When a workflow crosses systems, teams and judgment calls, AI has to be built around how your business operates.
Starting point
Scope of impact
How it is deployed
Production timeline
What you own at the end
AI SaaS Tool
The tool's capabilities(you bend the work to the product)
One capability
Another system to adopt(your team needs to learn)
Months of adoption(installed fast, absorbed slowly)
A subscription
Automation Projects
A list of disconnected tasks(whatever looks automatable)
Individual tasks
Glued on at the edges(breaks when a tool changes)
Slow to production(early demos break)
Custom scripts
Your bottlenecks(workflows constraining growth)
End-to-end workflows
Embedded into operation(systems, data and teams)
Four weeks(production-grade key workflows)
A production capability
Bring your bottleneck. Leave with a system concept.
Book a working sessionIn a free 30-minute working session, we'll map one painful workflow and send you a clear system concept within two working days.
Frequently Asked Questions
What does Revensi actually build?
We build custom AI systems, agents, internal tools, integrations and software around specific business workflows. The architecture follows the bottleneck, not a predefined product. The deliverable is a production capability embedded into your operation, not a prototype, strategy deck or isolated AI experiment.
What does forward-deployed AI engineering mean in practice?
We work directly with the people who own the workflow and build inside the reality of your business. That means understanding how work actually happens across teams, systems, data, approvals and exceptions, then designing and deploying the production system around it. We stay close to the problem from discovery through implementation rather than handing over recommendations for someone else to build.
How does Revensi work with our internal teams?
We embed alongside the people who understand and own the workflow. Depending on the project, that may include operators, functional leaders, engineering, data, IT and security. Your team provides the operational context, access and decisions; Revensi leads the system design, engineering, integration and deployment.
Can you work within our existing systems, infrastructure and security requirements?
Yes. We build around the systems and architecture already running your business. We integrate with existing software and approved data sources, work within your cloud and security requirements, retain human approval where needed and use private or locally deployed models when privacy, residency or control demands it.
Where do we start?
Start with the Sprint when the bottleneck and target workflow are already clear and the goal is working software in production. Start with the two-week AI Opportunity Roadmap when several workflows are competing for investment, priorities are contested, the data is unproven or the commercial case still needs to be established.
How can something be live in four weeks?
Because we launch a focused production system, not attempt to replace an entire platform. We map the workflow and its constraints, design the system and approval boundaries, connect it to your existing tools, test it against real scenarios and launch a focused capability into production.
How do you prove the system works?
We define the baseline, acceptance criteria and business measure before development begins. Evaluation covers the complete workflow, including reliability, human review, cost and latency. After launch, we measure adoption, operational performance and the selected business result separately.
What do we own?
You own the system built for your business: its code, configuration, data, integrations and deployment. You also receive the documentation and handoff required to operate it. Revensi retains only its existing reusable libraries and engineering tools, with any components used in your system licensed for continued operation.
Have more questions? Talk to us.
Build Capacity To Grow. Become AI Native.
Bring the workflow costing you the most. We'll map the bottleneck and show you what the AI system could look like.