Pilots that never left the demo
A proof of concept impressed the leadership team months ago. It still isn’t connected to a real system, a real user or a real process.
A fractional AI partner with an engineering team behind it
We put AI into production on top of the systems you already run, with part-time AI leadership from Diffco’s CTO and senior AI architects. Together we decide which workflows to automate first, which systems an agent can safely touch, and what to buy or build. When the plan says build, a senior Diffco team ships the agent layer.
Products we developed are used by
Awards and client reviews
- Top AI Development Company
- Top 10 Software Developers
- Top AI Developers
in California
- Top Staff Augmentation Company
Diffco handled discovery for two complex health tech AI products for us. They’re technically sharp, honest about what’s actually worth building, and easy to work with. They moved fast without cutting corners and understood the healthcare space. Highly recommend.
Mark MagazuPrincipal at M3 Veterinary Innovation Advisors
When you need one
The board wants AI.
Your team is busy running the business.
Most mid-size companies already have the systems, the data and the people. What’s missing is someone whose job is to decide where AI pays off, make it safe to run on real data, and see it through to production.
Every vendor now sells an agent
Your CRM, ERP and helpdesk each pitch their own. Someone has to decide which are worth paying for, which to build, and how they fit together.
Data nobody has mapped
What an agent needs lives in the ERP, in SharePoint, in ticket history and in people’s heads. Nobody knows yet what’s usable.
Security says no at the last step
Legal, security and audit see the AI project for the first time right before launch. In a regulated business, that’s where projects stop.
A CTO whose roadmap is already full
Your technical leadership is running the platform, the migration and the team. AI keeps landing on their desk as the eighth priority.
No way to tell if it’s working
Nobody defined what good looks like, so nobody can say whether the AI spend pays off or which use case to fund next.
The honest version
Some AI ideas work better as a rule in a workflow tool you already have, a report, or a feature your vendor already ships. We say that on the first call when it’s true. An agent is the right answer when the work repeats, the judgment behind it is written down somewhere, and a person can check the result.
How a fractional AI engagement runs
Decide where AI pays off first.
Then build it on top of what you already run.
AI assessment: we arrive with a first draft
1–2 weeks. Under NDA, before the first workshop, our agents read the docs, process maps, sample data and past vendor proposals you share. A senior AI architect turns them into a first draft of your roadmap. You leave with a ranked use-case list and a 90-day plan you can use with or without us.
Best for:Every engagement starts here.
Ongoing AI leadership
A fixed monthly allocation of CTO and AI architect time to own your AI decisions, from use cases and vendors to governance and board updates.
Best for:Companies with AI decisions in flight and no one who owns them.
Build the agent layer, if you choose to
When the roadmap calls for building, the same architect leads a senior Diffco team: agents and AI features connected to your ERP, CRM, helpdesk and data, with a person signing off where it matters. One accountable firm, no handoff.
Best for:Teams that want the roadmap executed by the people who wrote it.
Enable your team
We set up how your engineers build with AI agents, how changes get checked and how an agent’s work is reviewed, then coach them until they run it themselves.
Best for:Companies building their own AI capability.
Hand over
When you hire a head of AI or your team is ready, we hand over the documentation, decision logs, evaluations and runbooks. Then we step back, or stay on as your delivery partner.
Best for:The end state every fractional engagement should plan for.
What’s included
The four AI decisions someone has to own
A ranked AI use-case portfolio
Which workflows to automate first, what each is worth, what data it needs and what it costs to run, tied to business goals rather than the latest demo.
Architecture, model and vendor decisions
Build, buy or use your vendor’s built-in AI; which models, where they run, how agents connect to your systems. Every decision is written down with its alternatives, and expensive-to-reverse choices are flagged first.
Governance your security team can sign off on
Data-access rules, human sign-off points, audit trail, evaluation standards and a model-risk register, set up for regulated environments from the first week.
Leadership and board reporting
One page showing what’s live, what it’s saving, what’s waiting on a decision and what needs a second look, plus someone on the call who can answer the hard follow-up.
Where it pays off first
Six places agents usually earn their keep
Agents do best on repetitive work that already follows rules, runs through systems you own, and ends in something a person can check.
Document intake
Invoices, claims, applications, contracts: read, classified, checked against your rules, with exceptions routed to a person.
Service and support triage
Tickets and emails sorted, enriched from your CRM and order history, simple cases drafted, the rest handed over cleanly.
Operations and field work
Scheduling, dispatch, job notes and follow-ups connected across your field-service, CRM and billing systems.
Finance back office
Reconciliation, anomaly flags, collections follow-up and month-end prep, with a person approving anything that moves money.
Sales and account operations
The CRM kept current from email and calls, account research before meetings, proposals drafted from your own past work.
Compliance and audit evidence
Evidence pulled from the systems that hold it, gaps flagged before the auditor finds them, every step logged.
Choosing the model
AI consultancy, platform vendor,
or a partner that builds?
AI strategy consultancyYour platform vendor’s AIDiffco fractional AI partner
AI strategy and roadmap
Their product’s roadmapCTO / senior AI architect
Their product’s roadmapCTO / senior AI architectA team that buildsYou hire or contract separatelyInside their platform onlySenior team, when the plan calls for it
Senior team, when the plan calls for itWorks across your systemsAdvice onlyOne platformAgent layer across ERP, CRM, helpdesk and data
Agent layer across ERP, CRM, helpdesk and dataNeutral on models and vendorsConflict of interestYes, and we can oversee your other vendors
Conflict of interestYes, and we can oversee your other vendorsCost modelProject or retainerLicense plus usageMonthly leadership allocation; build priced separately after the assessment
Monthly leadership allocation; build priced separately after the assessmentBest whenYou need a strategy documentOne platform covers the use caseYou need AI in production across the systems you run
You need AI in production across the systems you run
How we build
Deciding what to automate is the hard part. Building it is the fast part now.
Choosing which workflow to automate first, which systems an agent may write to, and which ideas to drop is where AI budgets are won or lost. That’s the job of a fractional AI partner.
When the plan calls for building, the same method runs the build. Senior engineers decide, 100+ AI agents per engineer build around the clock inside a living plan with automatic checks, and a person reviews the result before it ships. Every decision that matters is written down, the record your auditors and board will ask for.
The loop, in a regulated business
- You say what you want
- We show what it affects
- You approve
- Agents build inside the plan, with automatic checks
- A person reviews the result before it ships
- 1–2 weeksto a ranked use-case list and a 90-day plan
- Everyarchitecture decision written down with its alternative
- 100+AI agents per engineer when we build
- Yoursthe roadmap, decision log and code, from week one
Why a fractional AI partner from Diffco
AI judgment from a firm that still ships production software.
Leadership that runs AI in production today
Eugene Nasonov, Diffco’s CTO and co-founder, still directs delivery on client systems, where our engineers work with 100+ AI agents each. His advice comes from current practice, not conference talks.
18+ years, 1,450+ products
Diffco has shipped software since 2008, including for healthcare and finance clients. We know what a security review will ask before it asks.
An agent layer, not a rip-and-replace
We build on top of your ERP, CRM and helpdesk. Your systems stay the source of truth; agents do the work in between.
We’ll tell you when an agent is the wrong tool
Sometimes the answer is a rule, a report or a feature your vendor already ships. We’d rather say so than sell you a build.
Hands available when you need them
When the roadmap says build, the people who wrote it can build it. Most AI advisors hand you a strategy and a list of vendors.
Neutral on models and platforms
Claude, OpenAI or Gemini, on AWS or your own cloud. Choices follow your data, cost and risk.
AI product engineering · SaaS
Maze’s AI Moderator, live in production, with its interview interface rebuilt in WebGL
Maze wanted user research without a researcher in the room. Diffco delivered the AI Moderator inside Maze’s own product and stack, including the live participant interface: rebuilt in WebGL so its listening, thinking and responding states stay smooth while a conversation runs.
- 20 languagesLive in production, running interviews in 20 languages.
- 35 customersIn the beta, ahead of general availability.
- By pull requestDelivered inside Maze’s own monorepo and review process.
Two ways to engage
Start with the assessment.
Decide the rest with the roadmap in hand.
AI assessment
1–2 weeks
A senior AI architect turns what you share into your roadmap: ranked use cases, the systems and data each one needs, a risk register, a data-access and security plan, and a build, buy or skip call on every use case. Any estimate comes as a range, with the open questions that make it wide.
Fixed scope, agreed up front- The roadmap is yours in full: use it with any team, including your own
Fractional AI partner
A monthly allocation of CTO and AI architect time covering the use-case portfolio, architecture and vendor decisions, governance and leadership reporting. Add a Diffco delivery team when the roadmap calls for building.
- Allocation set after the assessment, based on the decisions in flight
- Works alongside your CTO, IT team and existing vendors
- Transition plan to an in-house AI lead built in
Success stories of our clients
We built VetLeo, an AI companion pet owners ask anything about their pet
We set up AI-native development across RedTrack’s ad-tracking platform
We lead end-to-end development of an AI-enhanced ERP for U.S. K–12 school districts
Ongoing engineering support for an AI receipt platform
We’re building Raivan, an AI-powered next-gen veterinary PMS for M3 VIA
We built VetLeo, an AI companion pet owners ask anything about their pet
We set up AI-native development across RedTrack’s ad-tracking platform
Explore our
amazing case studies
Let’s build something
great together.
Frequently Asked Questions
Part-time AI leadership plus a team that can build. A fractional AI partner owns the AI decisions a mid-size company needs made: which use cases to fund, which models and vendors, how agents connect to existing systems, how it’s all governed, without a full-time Chief AI Officer. At Diffco the role is filled by our CTO or a senior AI architect, with a delivery team available when the roadmap calls for building.
The fractional CTO is for companies that don’t have technical leadership yet. The fractional AI partner is for companies that do (a CTO or CIO, a stack, an IT team) and need someone to own AI specifically, working alongside the leadership already in place.
Because AI is a full job on top of theirs. We take the use-case analysis, vendor evaluations, architecture reviews and governance work off their desk and bring them decisions, not homework. They stay in charge.
Your ERP, CRM, helpdesk and data warehouse stay where they are and remain the source of truth. Agents sit between them: they read from those systems, do the repetitive work, write back through the same permissions a person would have, and hand the judgment calls to a person.
When a rule in a workflow tool you already have does the job, when the data it needs doesn’t exist or can’t be trusted, when nobody can check the result, or when a mistake costs too much to allow. We say so in the assessment and recommend the cheaper answer.
No. The assessment recommends what’s right: sometimes a feature your vendor already ships, sometimes your own team, sometimes another firm. When it is a Diffco build, it’s priced separately and you decide.
Agents get the minimum access the work needs, through the same controls your people use. Every action is logged, and a person signs off where the stakes are real. Your requirements, whether SOC 2, HIPAA, PCI DSS or your own policies, become rules every agent reads before it starts, enforced by automatic checks on every change. We work to SOC 2-aligned practices with HIPAA- and GDPR-aware delivery, and where your data is stored and processed is agreed in writing before work starts.
The assessment is a fixed scope agreed up front. The partnership is a monthly allocation of CTO and architect time, set after the assessment based on the decisions in flight. Any build is priced separately, with the estimate given as a range and the open questions that make it wide.
You do, in full, from the first week. Use cases, specifications, the decision log, evaluations and acceptance standards are plain files that live beside your code, yours to keep and take to any team, including a future head of AI.
Need other services?
Fractional CTO ServicesProduct and technical direction, architecture, hiring and AI strategy from Diffco’s CTO, with a senior team to build it.
Forward Deployed EngineerA senior Diffco AI engineer embedded in your team, backed by an architect, who takes your AI use case from pilot to production.
AI-Driven Product DiscoveryTwo weeks to answer “should we build this, and what would it cost to run,” before you spend six months finding out.
AI Agents DevelopmentCustom agents and multi-agent systems that do real work inside your CRM, EHR, ERP, and internal tools.
AI & ML DevelopmentML, RAG, computer vision, and copilots, engineered to production standards with Production-Ready AI Engineering.
