Databotiq is an AI-first build studio for startups and small teams. We build AI workflow automations, custom and voice agents, knowledge assistants, and document processing. A Rapid POC is a working prototype on your real data, in 14 days, so you decide with evidence instead of slides.
The pattern is the same across teams we talk to. A tool gets bought before the problem is defined, the data does not match the demo, the project quietly slips, and a year later there is no working software and no one wants to talk about it.
of AI pilots never produce measurable ROI in production.
of small business owners say their AI tools saved them no real time after 90 days.
is buying the wrong tool first, not technical complexity. So we built Rapid POC to invert that.
So we flipped it. We build the smallest working version of your idea, on your data, in 14 days. Before you commit to a bigger build.
Sources: AI project failure rates and SMB AI ROI data, 2025 to 2026 (RAND, Pendo, Folio3, AI Lab Australia, Business.com SMB outlook).
A Rapid POC is a fixed-scope working prototype. We build an app shell, a backend connected to your real data, and a small operator surface to demo it. You use it to answer the questions an RFP cannot: accuracy on your data, speed in your environment, and what production would actually take.
Fixed-scope build on your stack. Not a multi-quarter science fair, not a slide deck dressed up as a roadmap.
We quote the POC after a short scoping call, in writing. No surprises mid-sprint, no scope creep without a written change request.
We integrate where the value actually lives. Your CRM, your Shopify, your shared inbox, your spreadsheets, your portals.
Each card has a live preview and a short definition. If you are not sure which one fits, we will map it on the scoping call and tell you honestly.
End-to-end automations across the tools you already use, with model judgment where rules alone are not enough.
End-to-end automations across the tools you already use, with model judgment where rules alone are not enough.
Agents that take real actions in your tools, with memory, fallbacks, and a human in the loop where it matters.
AI voice agents for inbound calls, qualification, scheduling, and callbacks. Real-time, interruptible, and tied to your CRM.
Hi, I'm looking at the two-bedroom on Smith Street. Is it still available this weekend?
It is, the Saturday eleven AM viewing has two slots left. Want me to book one and send the address by SMS?
Internal and customer-facing assistants that actually look things up, double-check themselves, and cite sources.
Bundled items are refundable within 30 days when returned together. International orders follow the same window, with shipping costs not refunded. (Refund policy v3, International T&C 2.4)
Your invoices, receipts, contracts, and claim forms read and routed automatically, with confidence scoring and human review on the close calls.
Your messy data, made useful. PDFs, email threads, voice notes, photos, and spreadsheets turned into structured records your tools can use.
AI in 2026 is not the AI in your training course from last year. The bar moved on voice, agents, retrieval, and multimodal in a big way. You do not need to know any of this to work with us. We will pick the right pieces inside the Rapid POC and explain them in plain English.
Agents that pick the next step instead of running a fixed script. Better for messy real-world ops than 2024-style chatbots.
Real-time speech with barge-in handling and conversation memory. The bar moved fast in the last twelve months and most older voice tooling cannot keep up.
Model Context Protocol lets agents share context with each other and with your tools, with governance you can actually audit.
Models that read text, voice, images, and PDFs together, so a single agent can handle a support email with screenshots without three handoffs.
Assistants that rewrite weak queries, check their own answers, and follow up across multiple sources. A big upgrade on classic RAG for anything non-trivial.
Agents that work for minutes or hours, not seconds, with checkpoints you can inspect along the way.
These are the industries we have built for the most. We work with teams wherever they are, and if yours is not on the list, the same patterns probably apply, ask us.
Support agents on your inbox, returns and refund flows, product Q&A on the storefront, and ad and content automations on Shopify, Amazon, and major marketplaces.
Client onboarding automation, document review for contracts and statements, and an internal knowledge assistant that actually knows your playbooks.
Tier-one support agent with smart escalation, onboarding flows that actually finish, and churn-signal copilots for your customer success team.
Portal coordination across carriers, document parsing for invoices and bills of lading, and exception triage that does not lose the email thread.
Voice receptionist for inbound calls, lead qualifier on your listings, and a knowledge assistant for contracts, FAQs, and tenant questions.
Resume parsing and candidate ranking, JD enrichment, interview-scheduling agents that talk to candidates directly, and copilots that keep your CRM honest.
A note on regulated industries. We will run a Rapid POC for clinics, dental, wellness, billing ops, brokers, and similar teams. For production work that needs SOC 2, HIPAA, or ISO certifications, we hand off to a compliance-ready partner with a clean architecture and documentation pack. We are open about what we do and do not yet certify, so you avoid surprises later.
These are anonymised composites, not named clients. They show how we scope, what we measure inside a Rapid POC, and what production hardening usually includes for teams like yours.
Tier-one questions answered automatically with order context, returns flow, and a clean handoff when it is not sure.
Read the patternCalls answered, viewings booked into the CRM, and the recording stored. No more missed leads after hours.
Read the patternFourteen days of evidence on real data instead of a six-month vendor slide contest.
Read the patternFixed scope, fixed price. We build a working version on a slice of your real data. You get outputs you can show internally, plus an honest go or no-go recommendation.
We design the production version with your team. Systems involved, risks, the small set of metrics that define success, and what we will hand over at the end.
Weekly demos, integrations as deliverables, and a human review queue until the metrics stabilise. No big-bang launch, no surprises on go-live day.
Monitoring, evaluation loops, and quarterly reviews so the model, retrieval, and policies keep pace with your real traffic and your real customers.
We prove it on your data first, in 14 days. You see real outputs, real integrations, and real failure modes before you fund a bigger build.
Confidence scoring, fallback paths, audit trails, and clear ownership for the cases the model gets wrong. The boring parts that separate a demo from a system you can actually run.
We agree on three or four numbers up front, then instrument them so progress is visible every week. Not at the end of the project, when it is too late to course correct.
You should not have to take a vendor's word on security. Here is how we actually operate today, written so your operations, IT, and legal team can read it in one pass. For SOC 2, HIPAA, and ISO production work we hand off to a compliance-ready partner, and we will tell you that on the first call.
We can deploy into your AWS, Azure, or GCP tenancy when required, so sensitive workloads stay inside your boundary and your audit logs.
Mutual NDA for discovery, and a data processing agreement (DPA) before we touch production payloads at scale. We work with your paper or ours.
We map retention, erasure, and data residency to the regions you operate in. Documented, not assumed, so your privacy team has answers ready.
High-stakes decisions route to people. Models recommend, your policies and your owners approve.
We log prompts, tool calls, retrieved sources, and decisions, so you can explain outcomes to security, finance, and your customers.
We avoid single-vendor lock-in where your constraints allow, so you can swap models as pricing and capability shift over time.
Need a deeper security review, your own data processing agreement, or a specific compliance attestation? We are happy to walk through our controls on a 30-minute call.
Honest, specific answers. If something isn't covered here,ask us directly.
Databotiq is an AI-first build studio for startups and small to mid-sized teams. We design and ship AI workflow automations, custom and voice AI agents, agentic knowledge assistants, intelligent document processing (IDP), and unstructured data pipelines. We start every engagement with a Rapid POC on your stack so you can decide with evidence, not slideware.
A Rapid POC is a fixed-scope, fixed-price working prototype, built on your real data in about 14 days. You get an app shell, a backend connected to your systems, and a written go or no-go recommendation with the metrics that matter for your team. It is designed to answer the questions an RFP cannot: accuracy on your data, speed in your environment, and what production would actually take.
No, this is exactly who we build for. We focus on startups and small to mid-sized teams. Our Rapid POC was designed for teams that cannot afford a six-month experiment that goes nowhere, and our pricing reflects that.
We will run a Rapid POC for clinics, brokers, lenders, and similar teams. For production work that needs SOC 2, HIPAA, or ISO certifications, we hand off to a compliance-ready partner with a clean architecture and a documentation pack. We are open about what we do and do not yet certify, so you avoid surprises later.
No. We are model-agnostic. Inside the Rapid POC we tell you which model we picked and why (OpenAI, Anthropic, Google, or open-weight options like Llama and Qwen), and we keep the architecture portable so you can swap models as pricing and capability shift.
Most AI projects fail because the wrong tool gets bought before the problem is defined. We invert that. We build the smallest working version on your data first, with weekly increments and integrations treated as first-class work. You should expect working software, clear risks, and a handover path to production, not a strategy deck that ages on a shared drive.
Most engagements start with a Rapid POC, usually delivered in 14 days after access is in place. We provide a written quote after a short scoping call. Production phases are planned as fixed-scope sprints with weekly demos, so delivery stays predictable.
We default to least privilege, encryption in transit and at rest, customer-controlled environments when required, NDAs and data processing agreements before production handling, and full audit trails for model-driven decisions. Formal certifications and attestations vary by deployment, and we will document what applies to your program. We never claim a certification we cannot substantiate.
We are model-agnostic: OpenAI GPT family, Anthropic Claude, Google Gemini, and open-weight models like Llama and Qwen when self-hosting or cost matters. For documents we pair vision-language models with deterministic checks. For agents we use tool-calling models with orchestration patterns like graph-based workflows, structured state, and Model Context Protocol (MCP) where it is useful.
No. We work with founders, COOs, heads of operations, product owners, and customer experience leads all the time. We translate outcomes into architecture, propose sensible controls, and train your team on the runbooks we ship.
Yes. Integrations are core deliverables. We regularly connect to Shopify, Stripe, HubSpot, Salesforce, Zendesk, Intercom, Slack, Microsoft 365, Google Workspace, Notion, Sheets, and bespoke internal APIs. If your stack is older or stranger than that, we will tell you what is realistic in the Rapid POC.
We agree on a small set of quantitative metrics before work expands. Time saved, error rate, straight-through processing rate, cost per case, or revenue per rep, depending on the workflow. We instrument the system so those metrics are visible weekly, not only at the end of the project.
We design for failure first. Confidence thresholds, human review queues for low-confidence outputs, idempotent tool actions, kill switches for agents, and replayable logs. The goal is predictable behaviour under real traffic, not a leaderboard score on a toy dataset.
Book a 20-minute scoping call. We will tell you on the call whether a Rapid POC is the right next step, and send a written proposal within one business day if it is.
