AI IMPLEMENTATION FOR SMBS
I build practical AI implementations for SMBs and growth-stage companies: the operational tools, integrations, and automations that are too specific for off-the-shelf software and too small for big consulting firms. 6 to 12 weeks. Fixed price. Working code at the end.
Free, no sales pressure. If it is not a fit, I will point you toward the right vendor or off-the-shelf tool.
Shipped a private clinical AI assistant over a thousand-page guideline corpus, evaluation-gated before launch. Hybrid retrieval, refusal when grounding is weak, hosted entirely on their infrastructure. Every answer comes back with the source passage attached.
“Databit Solutions excelled at turning ambiguous objectives into a clear, actionable plan. For statistical analysis and machine learning, Databit Solutions will be my first call.”
Replaced a Tableau and Windsor stack with a custom finance intelligence platform for a multi-location clinic group. Direct QuickBooks integration, anomaly detection on cash and receivables, and plain-English queries against the warehouse. Hours of weekly reporting became a daily executive view leadership runs on every morning.
“Working with Databit was like hitting the jackpot! They took our ideas and turned them into a sleek and powerful workflow that we love.”
Built the ML and statistical intelligence layer for a precision-medicine biotech working on rare pediatric epilepsies. Longitudinal seizure trajectories on SCN2A and SYNGAP cohorts, surfaced as presentation-ready intelligence the clinical team uses in active development decisions.
Built an AI-ready research intelligence platform on a thousands-strong TBI cohort. Years of fragmented clinical evidence unified into one typed surface, plain-English queries against the cohort, automated reconciliation surfacing conflicts instead of hiding them. The clinical team runs their own analyses without an engineer in the loop. Several manuscripts in flight on insights this platform surfaced.
Built a custom intelligence platform for a California tree-nut farm management firm running properties up and down the state. Plain-English queries across operational, agronomic, and financial data; ML pattern recognition on yield, irrigation, and input streams from AgWorld, Semios, and HortAu. Daily-use system across field and office teams.
“Databit delivers highly sophisticated analytics, yet communicates findings in a clear and easy-to-understand way.”
Built a Slack-native chatbot for dispatchers and account managers at a mid-market North American freight broker. Tool-call grounding into live TMS, carrier portals, and SLA data, evaluation-gated against two hundred real dispatcher questions. Hours back per dispatcher per day, and new hires productive in weeks instead of months.
Built a causal incrementality engine for a specialty consumer brand portfolio, spanning every brand and every retail channel. Time-series counterfactual modeling, AI-assisted experiment design, and anomaly detection with attribution back to live campaigns. Marketing dollars rebalanced on real causal evidence rather than vendor scorecards.
A multi-component AI product for a vacation-rental analytics SaaS: a text-to-SQL agent for natural-language queries over the listings warehouse, occupancy-rate and revenue ML, LLM-powered review and photo analysis, competitor similarity scoring, and market-insight scrapers. Several internal APIs running in production, used by the platform's hosts to price and position their listings.
ACROSS THE STACK
From models to deploys, the tools that show up in real projects. Picked for fit, not loyalty.
Selected product builds across multi-tenant SaaS, fitness tech, and language learning. Each shipped to production with real users and real billing.
Multi-tenant AI marketing platform for indie SaaS founders. Eight specialized agents handle research, strategy, copy, content, ad creative, and ongoing optimization. Stripe subscriptions, Clerk auth, Postgres, BullMQ + Redis, Cloudflare R2, deployed on Railway. Real users, real billing.
Airbnb listing intelligence for serious short-term rental hosts. Daily rank tracking, AI-powered listing optimization, market analytics, and dynamic pricing, plus a Chrome extension that overlays the data on airbnb.com itself. Premium UX, fast, dark and light. Launching soon.
01
A 30-minute intro call, then a scoping conversation if there is a fit. I map your problem, your data, your existing tools, and your constraints. You get a written scope, fixed price, and timeline within a week.
02
I build, you review weekly. Every Friday you see working software, not slides. Scope changes get re-quoted in writing. No surprises, no scope creep, no budget blowouts.
03
Documentation, training, and source code transfer. Your team owns everything I build. I provide 30 days of post-handoff support to make sure the system runs without me.
This is for you if
This is not for you if
I agree on what gets built and what it costs before any work starts. No hourly billing, no scope creep, no surprise invoices.
You see real progress weekly, not slides or status reports. Scope changes get re-quoted in writing if anything shifts.
Source code, documentation, and team training. Your team owns the system. 30 days of post-handoff support included.
ALSO AVAILABLE
For teams that need a senior technical partner in the room week to week, not just for one project. Architecture and vendor decisions, hiring calls, AI strategy reviews, and the "are we doing this right?" questions. Monthly retainer, capped hours, rolling quarter.
I am Stijn, founder of Databit Solutions. I build AI tools, data systems, and operational software for SMBs across healthcare, agriculture, education, and professional services. I also lead applied AI safety research at AE Studio: mechanistic interpretability, gradient routing, deception detection, and evaluations of LLM subjective experience. I work with founders, operators, and clinical leadership directly. Every line of code, every integration, every decision goes through me.
I work directly with clients, not through account managers or junior consultants. I build the thing myself. The trade-off: I cannot take on unlimited scope, and I will not take on engagements where I am not the right fit. The benefit: faster decisions, better code, lower cost, and someone who actually understands what got shipped after it ships.
Yes for advisory retainers, specifically the Fractional AI CTO model: architecture decisions, vendor evaluations, hiring panels, and the "are we doing this right?" questions. Monthly cadence with capped hours. Not for on-call rotations, 24/7 pager coverage, or break-fix managed services.
The boring kind that ships and gets used. LLM integrations into existing systems. Custom agents and automations. ML and statistical models for specific operational problems. Data pipelines and analytics infrastructure. I avoid hype-driven work and projects where AI is not actually the right tool.
I will tell you. Plenty of "AI projects" turn out to be better solved with a script, a SQL query, or off-the-shelf software. A 30-minute call costs you nothing and you will leave with a clearer picture either way.
Usually I have a 4 to 8 week lead time before a new engagement starts. The discovery call is the first step: book it and I will share timing on the call.
Yes to NDAs (signed before any sensitive details are shared). For HIPAA work I sign BAAs and follow standard PHI handling practices. For other compliance regimes (SOC 2, GDPR, etc.) I will discuss requirements during discovery.
30-minute call. I will ask about your problem, your tools, and your constraints. If there is a fit, you will get a written scope within 48 hours. If not, I will point you somewhere better.
Book a 30-minute call
