Est. 2003 · Mississauga, ONRetrieve quote
Softbase Solutions
Ch. 04 / Practice III · Custom AI productsMississauga · ON · Since 2003

Custom AI products that earn their keep.

We design, build, and operate retrieval-augmented copilots, agents, and AI features — with evaluation harnesses so you know they keep working.

Engagements

What we deliver

The ai solutions engagements we run most often.

  • 01

    AI Readiness Review

    Data, security, and ROI assessment to pick the right first project — and avoid the wrong ones.

  • 02

    RAG Copilots

    Knowledge assistants over your documents, tickets, and code — with citations and governance.

  • 03

    Agentic Workflows

    Multi-step agents with tools, memory, and guardrails for real, bounded business tasks.

  • 04

    Model Selection & Cost Tuning

    Pick the right model per workload, monitor token spend, and avoid runaway invoices.

  • 05

    Evaluation & Observability

    Golden sets, regression tests, and live quality monitoring so quality drift is visible, not surprising.

  • 06

    Responsible AI

    Content filters, PII handling, audit trails, and policy alignment for regulated environments.

Figure · Fig. 02

RAG that earns its keep.

The shape of a production retrieval-augmented copilot: data pipeline on the left, generation in the middle, evaluation on the right — with a feedback loop that catches quality drift before your users do.

Softbase reference RAG pipelineFive stages flow left to right: Data, Index, Retrieve, Generate, Evaluate. A feedback arrow returns from Evaluate to Index. A human-review branch hangs from Generate for high-stakes responses.FIG. 02 — RETRIEVAL-AUGMENTED COPILOTSTEP 01DataDocs · tickets · codeSTEP 02IndexEmbed · chunk · storeSTEP 03RetrieveTop-k · rerankSTEP 04GeneratePrompt · context · toolsSTEP 05EvaluateGolden set · driftFEEDBACK · GOLDEN-SET REGRESSIONHUMAN REVIEWHigh-stakes actions
— Fig. 02 · RAG pipeline with evaluation + human-in-the-loop

Method

How we engage.

A predictable cadence — from a written plan to running operations. You steer, we row.

  1. Step 1/4

    Discover

    A short workshop to align on success metrics. You walk away with a written plan in two weeks.

  2. Step 2/4

    Design

    Architecture, data model, and a thin slice in production — not a slide deck.

  3. Step 3/4

    Deliver

    Senior engineers ship in one-week increments you can review, test, and steer.

  4. Step 4/4

    Operate

    Runbooks, monitoring, and a clean handover — or we keep operating it for you.

Proof · in production

Outcomes from recent engagements.

Indicative results from delivery work in this practice. Numbers are anonymized; references available on request.

  1. 2 weeks

    from kickoff to a usable RAG pilot

    Running on the customer's Azure tenant with private endpoints from day one.

  2. 94%

    answer accuracy on the golden set

    Tracked weekly with regression alerts when quality drifts.

  3. −61%

    monthly token spend after model tuning

    Same quality bar, smaller / cached models on the hot paths.

Questions we hear

Frequently asked questions

Next

Dispatch

Have an AI idea? Let's stress-test it together.

In a 30-minute working session we'll size the problem, the data, and the smallest viable first slice.